2019 CVPR

下面是2019 CVPR文章的主题标签,文章列表来源于http://cvpr2019.thecvf.com/program/main_conference
Topic: Scene parsing; Object segmentation; Contour analysis; Object tracking; Action recognition; Video analysis; Human detection; Human parsing; Crowd analysis; Face recognition; Face parsing; Object recognition; Object detection; Saliency detection; Scene recognition; Image retrieval; 3D analysis; PointCloud analysis; Auto driver; Feature matching; Motion estimation; Stereo matching; Optical flow; Region matching; Image editing; Computational photography; Deep learning; Machine learning; GAN; Multimodel learning; Transfer learning; Reinforcement learning; Attack learning; Graph NN;

【Scene parsing】Auto-Deep Lab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

Chenxi Liu (Johns Hopkins University)*:

Liang-Chieh Chen (Google Inc.):

Florian Schroff (Google Inc.):

Hartwig Adam (Google):

Wei Hua (Google):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

【Scene parsing】Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation

Bohan Zhuang (The University of Adelaide)*:

Mingkui Tan (South China University of Technology):

Lingqiao Liu (University of Adelaide):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

【Scene parsing】Co-occurrent Features in Semantic Segmentation

Hang Zhang (Amazon Inc)*:

Han Zhang (Google):

Chenguang Wang (Amazon AI):

Junyuan Xie (Amazon):

【Scene parsing】Knowledge Translation and Adaptation for Efficient Semantic Segmentation

Tong He (The University of Adelaide):

Chunhua Shen (University of Adelaide)*: https://cs.adelaide.edu.au/~chhshen/

Zhi Tian (The University of Adelaide):

Dong Gong (The University of Adelaide):

Youliang Yan (Huawei):

Changming Sun (CSIRO Data61):

【Scene parsing】Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation

Yunhang Shen (Xiamen University):

Rongrong Ji (Xiamen University, China)*:

Yan Wang (Microsoft):

Yongjian Wu (Tencent Technology (Shanghai) Co.,Ltd):

Liujuan Cao (Xiamen University):

【Scene parsing】Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach

Yuhua Chen (ETH Zurich)*:

Wen Li (ETH Zurich):

Xiaoran Chen (ETH Zurich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Scene parsing】All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation

Wei-Lun Chang (National Chiao Tung University):

Hui-Po Wang (National Chiao Tung University):

Wen-Hsiao Peng (National Chiao Tung University):

Wei-Chen Chiu (National Chiao Tung University)*:

【Scene parsing】Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images

Yi Zhou (Inception Institute of Artificial Intelligence)*:

Xiaodong He (Inception Institute of Artificial Intelligence):

Lei Huang (the inception institute of artificial intelligence):

Li Liu (the inception institute of artificial intelligence):

Fan Zhu (Inception Institute of Artificial Intelligence):

Shanshan Cui (Inception Institute of Artificial Intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Scene parsing】Elastic Boundary Projection for 3D Medical Imaging Segmentation

Tianwei Ni (Peking University):

Lingxi Xie (Johns Hopkins University)*:

Huangjie Zheng (Shanghai Jiao Tong University):

Elliot K Fishman (JHMI):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Scene parsing】Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More

Jingwen Ye (Zhejiang University)*:

Yixin Ji (Zhejiang University):

Xinchao Wang (Stevens Institute of Technology):

Kairi Ou (Alibaba):

Dapeng Tao (Yunnan University):

Mingli Song (Zhejiang University):

【Scene parsing】Geometry-Aware Distillation for Indoor Semantic Segmentation

Jianbo Jiao (University of Oxford)*:

Yunchao Wei (UIUC):

Zequn Jie (Tencent AI Lab):

Honghui Shi (IBM | UIUC):

Rynson W.H. Lau (City University of Hong Kong):

Thomas Huang (UIUC):

【Scene parsing】Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation

Zhi Tian (The University of Adelaide)*:

Tong He (The University of Adelaide):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Youliang Yan (Huawei):

【Scene parsing】Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation

Chunfeng Song (CASIA, UCAS, CRIPAC)*:

Yan Huang (Institute of Automation, Chinese Academy of Sciences):

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Liang Wang (NLPR, China):

【Scene parsing】Dual Attention Network for Scene Segmentation

Jun Fu (National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences and University of Chinese Academy of Sciences)*:

Jing Liu (National Lab of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences):

Haijie Tian (BIT):

Yong Li (Business Growth BU, JD.com):

Yongjun Bao (JD.com):

Zhiwei Fang (National Lab of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences:

University of Chinese Academy of Sciences ):

Hanqing Lu (NLPR, Institute of Automation, CAS): http://people.ucas.ac.cn/~luhanqing

【Scene parsing】Structured Knowledge Distillation for Semantic Segmentation

Yifan Liu (University of Adelaide):

Ke Chen (Microsoft):

Chris Liu (Microsoft):

Zengchang Qin (Intelligent Computing & Machine Learning Lab, School of ASEE, Beihang University):

Zhenbo Luo ( Samsung Research Institute China-Beijing):

Jingdong Wang (Microsoft Research)*:

【Scene parsing】Context-Reinforced Semantic Segmentation

Yizhou Zhou (University of Science and Technology of China)*:

Xiaoyan Sun (Microsoft Research Asia):

Zheng-Jun Zha (University of Science and Technology of China):

Wenjun Zeng (Microsoft Research):

【Scene parsing】Adversarial Structure Matching for Structured Prediction Tasks

Jyh-Jing Hwang (International Computer Science Institute)*:

Tsung-Wei Ke (International Computer Science Institute):

Jianbo Shi (University of Pennsylvania): http://www.cis.upenn.edu/~jshi/

Stella X Yu (UC Berkeley / ICSI):

【Scene parsing】Pattern-Affinitive Propagation across Depth, Surface Normal and Semantic Segmentation

Zhenyu Zhang (Nanjing University of Sci & Tech)*:

Zhen Cui (Nanjing University of Science and Technology):

Chunyan Xu (Nanjing University of Science and Technology):

Yan Yan (Nanjing University of Science and Technology):

Nicu Sebe (University of Trento):

Jian Yang (Nanjing University of Science and Technology):

【Scene parsing】Not All Areas Are Equal: Transfer Learning for Semantic Segmentation via Hierarchical Region Selection

Ruoqi Sun (Shanghai Jiao Tong University)*:

Xinge Zhu (The Chinese University of Hong Kong):

Chongruo Wu (UC Davis):

Chen Huang (Carnegie Mellon University):

Jianping Shi (Sensetime Group Limited):

Lizhuang Ma (Shanghai Jiao Tong University):

【Scene parsing】KE-GAN: Knowledge Embedded Generative Adversarial Networks for Semi-Supervised Scene Parsing

Mengshi Qi (Beihang University)*:

Yunhong Wang (State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China): http://irip.buaa.edu.cn/Chinese.html

Jie Qin (Inception Institute of Artificial Intelligence):

Annan Li (Beijing University of Aeronautics and Astronautics):

【Scene parsing】Fickle Net: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference

Jungbeom Lee (Seoul National University):

Eunji Kim (Seoul National University):

Sungmin Lee (Seoul National University):

Jangho Lee (Seoul National University):

Sungroh Yoon (Seoul National University)*:

【Scene parsing】Scene Parsing via Integrated Classification Model and Variance-Based Regularization

Hengcan Shi ( University of Electronic Science and Technology of China)*:

Hongliang Li (University of Electronic Science and Technology of China):

Qingbo Wu (University of Electronic Science and Technology of China):

Zichen Song (University of Electronic Science and Technology of China):

【Scene parsing】An End-to-end Network for Panoptic Segmentation

huanyu liu (Zhejiang University)*:

Chao Peng (Megvii(Face++) Inc):

Changqian Yu (Huazhong University of Science and Technology):

Jingbo Wang (Peking University):

Xu Liu (The University of Tokyo):

Gang Yu (Face++):

Wei Jiang (Department of Control Science and Engineering, Zhejiang University):

【Scene parsing】Bidirectional Learning for Domain Adaptation of Semantic Segmentation

Yunsheng Li (UCSD)*:

Lu Yuan (Microsoft): http://research.microsoft.com/en-us/um/people/luyuan/index.htm

Nuno Vasconcelos (UC San Diego): http://www.svcl.ucsd.edu/

【Scene parsing】Attention-guided Unified Network for Panoptic Segmentation

Yanwei Li (Institute of Automation, CAS:

University of Chinese Academy of Sciences)*:

Zheng Zhu (Institute of Automation, Chinese Academy of Sciences):

Xinze Chen (Horizon Robotics):

Lingxi Xie (Johns Hopkins University):

Guan Huang (Horizon Robotics):

Xingang Wang (Institute of Automation, CAS):

Dalong Du (Horizon Robotics):

【Scene parsing】Building Detail-Sensitive Semantic Segmentation Networks with Polynomial Pooling

Zhen Wei (Institute of Information Engineering, the Chinese Academy of Sciences)*:

Jingyi Zhang (University of Electronic Science and Technology of China):

Li Liu (the inception institute of artificial intelligence):

Fan Zhu (Inception Institute of Artificial Intelligence):

Fumin Shen (UESTC):

yao sun (iie):

si liu (Beihang University):

Fan Zhu (the inception institute of artificial intelligence ):

Yi Zhou (Inception Institute of Artificial Intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Scene parsing】Adaptive Pyramid Context Network for Semantic Segmentation

Junjun He (SJTU):

Zhongying Deng (SIAT):

Lei Zhou (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Yali Wang (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Yu Qiao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)*: http://mmlab.siat.ac.cn/yuqiao/

【Scene parsing】SPNet: Semantic Projection Network for Zero-Label and Few-Label Semantic Segmentation

Yongqin Xian (Max Planck Institute Informatics)*:

Subhabrata Choudhury (Max-Planck Institute for Informatics):

Yang He (MPI Informatics):

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

Zeynep Akata (University of Amsterdam):

【Scene parsing】Seamless Scene Segmentation

Lorenzo Porzi (Mapillary Research):

Samuel Rota Bulò (Mapillary Research):

Aleksander Colovic (Mapillary Research):

Peter Kontschieder (Mapillary Research)*:

【Scene parsing】Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells

Vladimir Nekrasov (University of Adelaide / ACRV)*:

Hao Chen (The University of Adelaide):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

【Scene parsing】Panoptic Segmentation

Alexander Kirillov (Facebook AI Reserach)*:

Kaiming He (Facebook AI Research): http://research.microsoft.com/en-us/um/people/kahe/

Ross Girshick (FAIR): http://www.cs.berkeley.edu/~rbg/

Carsten Rother (University of Heidelberg): http://www.inf.tu-dresden.de/index.php?node_id=3517&ln=de

Piotr Dollar (FAIR): http://vision.ucsd.edu/~pdollar/

【Scene parsing】UPSNet: A Unified Panoptic Segmentation Network

Yuwen Xiong (Uber ATG:

University of Toronto)*:

Renjie Liao (University of Toronto):

Hengshuang Zhao (The Chinese University of Hong Kong):

Rui Hu (Uber):

Min Bai (University of Toronto):

Ersin Yumer (Uber ATG):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Scene parsing】Improving Semantic Segmentation via Video Propagation and Label Relaxation

Yi Zhu (UC Merced):

Karan Sapra (NVIDIA)*:

Fitsum Reda (NVIDIA):

Kevin Shih (NVIDIA):

Shawn Newsam (UC Merced):

Andrew Tao (NVIDIA):

Bryan Catanzaro (NVIDIA):

【Scene parsing】Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video

Samvit Jain (UC Berkeley)*:

Xin Wang (UC Berkeley):

Joey Gonzalez (Berkeley):

【Scene parsing】Semantic Correlation Promoted Shape-Variant Context for Segmentation

Henghui Ding (Nanyang Technological University)*:

Xudong Jiang (Nanyang Technological University):

Bing Shuai (Amazon):

Ai Qun Liu (Nanyang Technological University):

Gang Wang (Alibaba Group):

【Scene parsing】Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-high Resolution Images

Wuyang Chen (Texas A&M University)*:

Ziyu Jiang (Texas A&M University):

Zhangyang Wang (TAMU):

Kexin Cui (Texas A&M University):

Xiaoning Qian (Texas A&M University):

【Scene parsing】DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation

Hanchao Li (Beijing Institute of Technology)*:

Pengfei Xiong (Megvii(face++) Research):

Haoqiang Fan (Megvii Inc(face++)):

Jian Sun (Megvii Technology): http://research.microsoft.com/en-us/groups/vc/

【Scene parsing】A Cross-Season Correspondence Dataset for Robust Semantic Segmentation

Måns Larsson (Chalmers)*:

Erik Stenborg (Chalmers University):

Lars Hammarstrand (Chalmers university of technology):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

Torsten Sattler (Chalmers University of Technology):

Fredrik Kahl (Chalmers):

【Scene parsing】Cross-Modal Self-Attention Network for Referring Image Segmentation

Linwei Ye (University of Manitoba)*:

Mrigank Rochan (University of Manitoba):

Zhi Liu (Shanghai University, China):

Yang Wang (University of Manitoba):

【Scene parsing】Data augmentation with spatial and appearance transforms for one-shot medical image segmentation

Amy Zhao (MIT)*:

Guha Balakrishnan (MIT):

Fredo Durand (MIT): http://people.csail.mit.edu/fredo/

John Guttag (MIT):

Adrian V Dalca (MIT):

【Scene parsing】Customizable Architecture Search for Semantic Segmentation

Yiheng Zhang (University of Science and Technology of China):

Zhaofan Qiu (University of Science and Technology of China):

Jingen Liu (JD):

Ting Yao (JD AI Research)*:

Dong Liu (University of Science and Technology of China):

Tao Mei (AI Research of JD.com):

【Scene parsing】A Relation-Augmented Fully Convolutional Network for Semantic Segmentation in Aerial Scenes

Lichao Mou (DLR&TUM)*:

Yuansheng Hua ( German Aerospace Center):

Xiaoxiang Zhu (Technical University of Munich (TUM):

German Aerospace Center (DLR)):

【Scene parsing】Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology

Hiroki Tokunaga (Kyushu University)*:

Yuki Teramoto (Kyoto University):

Akihiko Yoshizawa (Kyoto University):

Ryoma Bise (Kyushu University):

【Scene parsing】Large Scale High-Resolution Land Cover Mapping with Multi-Resolution Data

Caleb Robinson (Georgia Institute of Technology)*:

Nebojsa Jojic (Microsoft Research):

Le Hou (Stony Brook University):

Kolya Malkin (Yale University):

Bistra Dilkina (University of Southern California):

Rachel Soobitsky (Chesapeake Conservancy):

Jacob Czawlytko (Chesapeake Conservancy):

【Object segmentation】SCOPS: Self-Supervised Co-Part Segmentation

Wei-Chih Hung (University of California, Merced)*:

Varun Jampani (Nvidia Research):

Sifei Liu (NVIDIA):

Pavlo Molchanov (NVIDIA):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【Object segmentation】Pose2Seg: Detection Free Human Instance Segmentation

Song-Hai Zhang (Tsinghua University):

Ruilong Li (Tsinghua University)*:

Xin Dong (Tsinghua University):

Paul Rosin (Cardiff University):

Zixi Cai (Tsinghua University):

Xi Han (Tsinghua University):

Dingcheng Yang (Tsinghua University):

Hao-Zhi Huang (Tencent AI Lab):

Shimin Hu (Tsinghua University): http://cg.cs.tsinghua.edu.cn/prof_hu.htm

【Object segmentation】MHP-VOS: Video Object Segmentation with Multiple Hypotheses Propagation

Shuangjie Xu (Huazhong University of Science and Technology):

Daizong Liu (Huazhong University of Science and Technology):

Linchao Bao (Tencent AI Lab)*:

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Pan Zhou ( Huazhong University of Science and Technology):

【Object segmentation】Spatiotemporal CNN for Video Object Segmentation

Kai Xu (University of Chinese Academy of Sciences):

Longyin Wen (JD Digits)*:

guorong Li (CAS):

Liefeng Bo (JD Finance):

Qingming Huang (University of Chinese Academy of Sciences):

【Object segmentation】Learning Attraction Field Representation for Robust Line Segment Detection

Nan Xue (Wuhan University):

Song Bai (University of Oxford):

Fudong Wang (Wuhan University):

Gui-Song Xia (Wuhan University)*:

Tianfu Wu (NC State University):

Liangpei Zhang ( Wuhan University):

【Object segmentation】Learning Inter-pixel Relations for Weakly Supervised Instance Segmentation

Jiwoon Ahn (DGIST):

Sunghyun Cho (DGIST):

Suha Kwak (POSTECH)*:

【Object segmentation】Amodal Instance Segmentation through KINS Dataset

Lu Qi (The Chinese University of Hong Kong)*:

Li Jiang (The Chinese University of Hong Kong):

Shu Liu (Tencent):

Xiaoyong Shen (Tencent):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Object segmentation】Learning-based Sampling for Natural Image Matting

Jingwei Tang (ETHZ & Disney Research)*:

Yagiz Aksoy (ETHZ):

Cengiz Oztireli (Disney Research):

Markus Gross (ETH Zurich):

Tunç Aydin (Disney Research):

【Object segmentation】Learning Unsupervised Video Object Segmentation through Visual Attention

Wenguan Wang (Inception Institute of Artificial Intelligence):

Hongmei Song (Beijing Institute of Technology):

Shuyang Zhao (Beijing Institute of Technology ):

Jianbing Shen (Beijing Institute of Technology)*: http://cs.bit.edu.cn/shenjianbing/

Sanyuan Zhao (Beijing Institute of Technology ):

Steven Hoi (SMU):

Haibin Ling (Temple University): http://www.dabi.temple.edu/~hbling/

【Object segmentation】SAIL-VOS: Semantic Amodal Instance Level Video Object Segmentation – A Synthetic Dataset and Baselines

Yuan-Ting Hu (University of Illinois at Urbana-Champaign)*:

Hong-Shuo Chen (UIUC):

Kexin Hui (UIUC):

Jia-Bin Huang (Virginia Tech):

Alexander Schwing (UIUC): http://www.alexander-schwing.de/

【Object segmentation】Learning Instance Activation Maps for Weakly Supervised Instance Segmentation

Yi Zhu (University of Chinese Academy of Sciences)*:

Yanzhao Zhou (University of Chinese Academy of Sciences):

Huijuan Xu (University of California, Berkeley):

Qixiang Ye (University of Chinese Academy of Sciences, China): https://ucassdl.cn/content/work/paper.html

David Doermann (University at Buffalo):

Jianbin Jiao (University of Chinese Academy of Sciences):

【Object segmentation】See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks

Xiankai Lu (Inception Institute of Artificial Intelligence):

Wenguan Wang (Inception Institute of Artificial Intelligence):

Chao Ma (Shanghai Jiao Tong University):

Jianbing Shen (Beijing Institute of Technology)*: http://cs.bit.edu.cn/shenjianbing/

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

Fatih Porikli (ANU): http://www.porikli.com/

【Object segmentation】Hybrid Task Cascade for Instance Segmentation

Kai Chen (The Chinese University of Hong Kong)*:

Jiangmiao Pang (Zhejiang University):

Jiaqi Wang (CUHK):

Yu Xiong (The Chinese University of HK):

Xiaoxiao Li (The Chinese University of Hong Kong):

Shuyang Sun (The University of Sydney):

Wansen Feng (Lille university ):

Ziwei Liu (The Chinese University of Hong Kong):

Jianping Shi (Sensetime Group Limited):

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

【Object segmentation】Fast User-Guided Video Object Segmentation by Interaction-and-Propagation Networks

Seoung Wug Oh (Yonsei Univeristy):

Joon-Young Lee (Adobe Research):

Ning Xu (Adobe Research):

Seon Joo Kim (Yonsei Univ.)*:

【Object segmentation】Fast Interactive Object Annotation with Curve-GCN

Huan Ling (University of Toronto):

Jun Gao (University of Toronto):

Amlan Kar (University of Toronto):

Wenzheng Chen (University of Toronto):

Sanja Fidler (University of Toronto)*:

【Object segmentation】End-to-End Recurrent Net for Video Object Segmentation

Carles Ventura (Universitat Oberta de Catalunya)*:

Míriam Bellver (Barcelona Supercomputing Center):

Andreu Girbau (Universitat Politècnica de Catalunya):

Amaia Salvador (Universitat Politècnica de Catalunya):

Ferran Marques (Universitat Politecnica de Catalunya):

Xavier Giro-i-Nieto (Universitat Politecnica de Catalunya):

【Object segmentation】Interactive Image Segmentation via Backpropagating Refinement Scheme

Won-Dong Jang (Harvard University)*:

Chang-Su Kim (Korea university): http://mcl.korea.ac.kr/people/professor/

【Object segmentation】LVIS: A Dataset for Large Vocabulary Instance Segmentation

Agrim Gupta (FAIR):

Piotr Dollar (FAIR): http://vision.ucsd.edu/~pdollar/

Ross Girshick (FAIR)*: http://www.cs.berkeley.edu/~rbg/

【Object segmentation】Deep Supervised Automatic Tooth Instance Segmentation and Identification from Cone Beam Computed Tomography Images

Zhiming Cui (HKU)*:

Changjian Li (The University of Hong Kong):

Wenping Wang (The University of Hong Kong):

【Object segmentation】Mask Scoring R-CNN

Zhaojin Huang (Huazhong University of Science and Technology):

Lichao Huang (Horizon Robotics):

Yongchao Gong (Horizon Robotics ):

Chang Huang (Horizon Robotics):

Xinggang Wang (Huazhong Univ. of Science and Technology)*: http://www.xinggangw.info/

【Object segmentation】Triply Supervised Decoder Networks for Joint Detection and Segmentation

Jiale Cao (Tianjin University):

Yanwei Pang (Tianjin University)*:

Xuelong Li (Northwestern Polytechnical University, China):

【Object segmentation】DARNet: Deep Active Ray Network for Building Segmentation

Dominic Cheng (University of Toronto)*:

Renjie Liao (University of Toronto):

Sanja Fidler (University of Toronto):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Object segmentation】A Late Fusion CNN for Digital Matting

Zhang Yunke (Zhejiang University):

Lixue Gong (Zhejiang university):

Lubin Fan (Alibaba Group):

Peiran Ren (Alibaba ):

Qixing Huang (The University of Texas at Austin):

Hujun Bao (Zhejiang University):

Weiwei Xu (Zhejiang unviersity)*:

【Object segmentation】Zig Zag Net: Fusing Top-Down and Bottom-Up Context for Object Segmentation

Di Lin (Shenzhen University)*:

Dingguo Shen (Shenzhen University):

Siting Shen (Shenzhen University):

Yuanfeng Ji (Shenzhen University):

Dani Lischinski (The Hebrew University of Jerusalem): http://www.cs.huji.ac.il/~danix/

Daniel Cohen-Or (Tel Aviv University):

Hui Huang (Shenzhen University): http://vcc.szu.edu.cn/~huihuang

【Object segmentation】Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery

Tao Sun (Tongji University):

Zonglin Di (Tongji University):

Pengyu Che (Tongji University):

Chun Liu (Tongji University):

Wang Yin (Tongji University)*:

【Object segmentation】Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation

Rakshith Shetty (Max Planck Institute of Informatics)*:

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

Mario Fritz (CISPA Helmholtz Center for Information Security): https://scalable.mpi-inf.mpg.de/

【Object segmentation】Actor-Critic Instance Segmentation

Nikita Araslanov (TU Darmstadt)*:

Constantin Rothkopf (TU Darmstadt):

Stefan Roth (TU Darmstadt): http://www.igp.ethz.ch/photogrammetry/

【Object segmentation】Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics

Yaron Meirovitch (MIT CSAIL)*:

Lu Mi (MIT):

Hayk Saribekyan (MIT):

Alexander Matveev (MIT):

David Rolnick (MIT):

Nir Shavit (Massachusetts Institute of Technology):

【Object segmentation】Proposal-free instance segmentation with a clustering loss function

Davy Neven (KULeuven)*:

Bert De Brabandere (KU Leuven):

Marc Proesmans (KU Leuven):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Object segmentation】Deep Instance Co-segmentation by Co-peak Search and Co-saliency Detection

Kuang-Jui Hsu (Academia Sinica)*:

Yen-Yu Lin (Academia Sinica):

Yung-Yu Chuang (National Taiwan University):

【Object segmentation】Bubble Nets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames

Brent Griffin (University of Michigan)*:

Jason J Corso (University of Michigan):

【Object segmentation】A Generative Appearance Model for End-to-end Video Object Segmentation

Joakim Johnander (Linköping University)*:

Martin Danelljan (ETH Zurich):

Emil Brissman (Linköping University):

Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence):

Michael Felsberg (Linköping University): http://users.isy.liu.se/cvl/mfe/

【Object segmentation】FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

Paul Voigtlaender (RWTH Aachen University)*:

Yuning Chai (Alphabet):

Bastian Leibe (RWTH Aachen University-): http://www.vision.rwth-aachen.de/

Florian Schroff (Google Inc.):

Hartwig Adam (Google):

Liang-Chieh Chen (Google Inc.):

【Object segmentation】Learning Multi-Class Segmentations From Single-Class Datasets

Konstantin Dmitriev (Stony Brook University)*:

Arie Kaufman (Stony Brook University):

【Object segmentation】Beyond Gradient Descent for Regularized Segmentation Losses

Dmitrii Marin (University of Waterloo)*:

Meng Tang (University of Waterloo):

Ismail Ben Ayed (ETS Montreal):

Yuri Boykov (University of Waterloo): http://www.csd.uwo.ca/~yuri/

【Object segmentation】Scale-Aware Multi-Level Guidance for Interactive Instance Segmentation

Soumajit Majumder (University of Bonn)*:

Angela Yao (National University of Singapore):

【Object segmentation】Interactive Full Image Segmentation

Eirikur Agustsson (Google)*:

Jasper Uijlings (Google Research):

Vittorio Ferrari (Google Research): http://groups.inf.ed.ac.uk/calvin/index.html

【Object segmentation】Learning Active Contour Models for Medical Image Segmentation

Xu Chen (University of Liverpool):

Bryan M. Williams (University of Liverpool):

Srinivasa Vallabhaneni (University of Liverpool and Royal Liverpool & Broadgreen University Hospitals NHS Trust):

Gabriela Czanner (Liverpool John Moores University):

Rachel Williams (University of Liverpool):

Yalin Zheng (University of Liverpool)*:

【Object segmentation】Large-scale interactive object segmentation with human annotators

Rodrigo Benenson (Google)*: http://rodrigob.github.io/

Stefan Popov (Google):

Vittorio Ferrari (Google Research): http://groups.inf.ed.ac.uk/calvin/index.html

【Object segmentation】Object Counting and Instance Segmentation with Image-level Supervision

Hisham Cholakkal (Inception Institute of Artificial Intelligence)*:

Guolei Sun (Inception Institute of Artificial Intelligence):

Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Object segmentation】End-to-End Learned Random Walker for Seeded Image Segmentation

Lorenzo Cerrone (HCI/IWR uni heildelberg)*:

Alexander Zeilmann (IWR uni heidelberg):

Fred Hamprecht (Heidelberg Collaboratory for Image Processing):

【Object segmentation】Context-aware Spatio-recurrent Curvilinear Structure Segmentation

Feigege Wang (Fuzhou University):

Yue Gu (Fuzhou University):

Wenxi Liu (Fuzhou University)*:

Yuanlong Yu (Fuzhou University):

Shengfeng He (South China University of Technology):

Jia Pan (City University of Hong Kong):

【Contour analysis】Deep SDF: Learning Continuous Signed Distance Functions for Shape Representation

Jeong Joon Park (University of Washington)*:

Peter R Florence (MIT):

Julian Straub (Facebook Reality Labs):

Richard Newcombe (Facebook):

Steven Lovegrove (Facebook):

【Contour analysis】ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape

Fabian Manhardt (TU Munich):

Wadim Kehl (Toyota Research Institute)*:

Adrien Gaidon (Toyota Research Institute):

【Contour analysis】Shape Unicode: A Unified Shape Representation

Sanjeev Muralikrishnan (Adobe)*:

Vladimir Kim (Adobe):

Matthew Fisher (Adobe Research):

Siddhartha Chaudhuri (Adobe Research):

【Contour analysis】Local detection of stereo occlusion boundaries

Jialiang Wang (Harvard University)*:

Todd Zickler (Harvard University):

【Contour analysis】Bi-Directional Cascade Network for Perceptual Edge Detection

Jianzhong He (Peking University):

Shiliang Zhang (Beijing University)*:

Ming Yang (Horizon Robotics):

Yanu Shan (Beijing Horizon information Technology Co.,ltd):

Tiejun Huang (Peking University): http://www.jdl.ac.cn/~tjhuang/index-en.html

【Contour analysis】Scene Categorization from Contours: Medial Axis Based Salience Measures

Morteza Rezanejad (Mcgill university )*:

Gabriel Downs (Mc Gill University):

John Wilder (University of Toronto):

Dirk Bernhardt-Walther (University of Toronto):

Sven Dickinson (University of Toronto):

Allan Jepson (Samsung):

Kaleem Siddiqi (Mc Gill University):

【Contour analysis】Deep Flux for Skeletons in the Wild

Yukang Wang (Huazhong University of Science and Technology):

Yongchao Xu (Huazhong University of Science and Technology)*:

Xiang Bai (Huazhong University of Science and Technology): http://cloud.eic.hust.edu.cn:8071/~xbai/

Stavros Tsogkas (University of Toronto):

Sven Dickinson (University of Toronto):

Kaleem Siddiqi (Mc Gill University):

【Contour analysis】Texture Net: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes

Jingwei Huang (Stanford University)*:

Haotian Zhang (Stanford University):

Li Yi (Stanford):

Thomas Funkhouser (Princeton University and Google, Inc.):

Matthias Niessner (Technical University of Munich): http://niessnerlab.org/publications.html

Leonidas Guibas (Stanford University):

【Contour analysis】A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images

Jiapeng Tang (South China University of Technology):

Xiaoguang Han (Shenzhen Research Institute of Big Data, the Chinese University of Hong Kong (Shenzhen))*:

Junyi Pan (South China University of Technology):

Kui Jia (South China University of Technology):

Xin Tong (Microsoft):

【Contour analysis】RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion

Muhammad Sarmad (KAIST)*:

Hyunjoo Jenny Lee (KAIST-BMMLab):

Young Min Kim (KIST):

【Contour analysis】Learning Implicit Fields for Generative Shape Modeling

Zhiqin Chen (Simon Fraser University)*:

Hao Zhang (Simon Fraser University):

【Contour analysis】A Robust Local Spectral Descriptor for Matching Non-Rigid Shapes with Incompatible Shape Structures

Yiqun Wang (NLPR, Institute of Automation, Chinese Academy of Sciences)*:

Jianwei Guo (NLPR, Institute of Automation, Chinese Academy of Sciences):

Yan Dong-Ming (NLPR, CASIA):

Kai Wang (CNRS, GIPSA-lab):

Xiaopeng Zhang (Institute of Automation, Chinese Academy of Sciences):

【Contour analysis】Object Instance Annotation with Deep Extreme Level Set Evolution

Zian Wang (Tsinghua University)*:

David Acuna (University of Toronto):

Amlan Kar (University of Toronto):

Huan Ling (University of Toronto):

Sanja Fidler (University of Toronto):

【Contour analysis】Isospectralization, or how to hear shape, style, and correspondence

Luca Cosmo (University of Venice):

Maks Ovsjanikov (Ecole polytechnique): http://www.lix.polytechnique.fr/~maks/publications.html

Mikhail Panine (Ecole polytechnique):

Arianna Rampini (Sapienza University of Rome)*:

Michael Bronstein (Università della Svizzera Italiana):

Emanuele Rodola (Sapienza University of Rome):

【Contour analysis】A Theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction

Shumian Xin (Carnegie Mellon University):

Sotiris Nousias (University College London):

Kyros Kutulakos (University of Toronto):

Aswin Sankaranarayanan (Carnegie Mellon University):

Srinivasa G Narasimhan (Carnegie Mellon University):

Ioannis Gkioulekas (Carnegie Mellon University)*:

【Contour analysis】Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes

Xiaogang Wang (State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering,Beihang University): http://www.ee.cuhk.edu.hk/~xgwang/

Kai Xu (National University of Defense Technology)*:

Yahao Shi (State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering,Beihang University):

Bin Zhou (State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering,Beihang University):

Xiaowu Chen (): http://arts.buaa.edu.cn/index.htm

Qinping Zhao (State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering,Beihang University):

【Contour analysis】Part Net: A Recursive Part Decomposition Network for Hierarchical Segmentation of 3D Shapes

Fenggen Yu (Nanjing University):

Kun Liu (Nanjing University):

Yan Zhang (Nanjing University):

Chenyang Zhu (Simon Fraser University):

Kai Xu (National University of Defense Technology)*:

【Contour analysis】Convolutional Recurrent Network for Road Boundary Extraction

Justin JL Liang (Uber ATG)*:

Namdar Homayounfar (University of Toronto):

Wei-Chiu Ma (MIT):

Shenlong Wang (Uber ATG, University of Toronto):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Contour analysis】Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboids

Despoina Paschalidou (MPI-IS Tuebingen )*:

Ali O Ulusoy (Microsoft):

Andreas Geiger (MPI-IS and University of Tuebingen):

【Contour analysis】Fast Draw: Lane Detection by a Sequential Prediction Network

Jonah Philion (ISEE Inc.)*:

【Contour analysis】Unsupervised Part-Based Disentangling of Object Shape and Appearance

Dominik Lorenz (Heidelberg University):

Leonard Bereska (Heidelberg University):

Timo Milbich (Heidelberg University)*:

Bjorn Ommer (Heidelberg University):

【Contour analysis】Devil is in the Edges: Learning Semantic Boundaries from Noisy Annotations

David Acuna (University of Toronto)*:

Amlan Kar (University of Toronto):

Sanja Fidler (University of Toronto):

【Contour analysis】PDE Acceleration for Active Contours

Minas D Benyamin (Georgia Institute of Technology )*:

Ganesh Sundaramoorthi (Kaust):

Anthony Yezzi (Georgia Tech):

【Object tracking】Unsupervised Deep Tracking

Ning Wang (University of Science and Technology of China)*:

Yibing Song (Tencent AI Lab):

Chao Ma (Shanghai Jiao Tong University):

Wengang Zhou (University of Science and Technology of China):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Houqiang Li (University of Science and Technology of China):

【Object tracking】Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Zhen He (NUDT)*:

Jian Li (NUDT):

Daxue Liu (NUDT):

Hangen He (NUDT):

David Barber (UCL):

【Object tracking】Fast Online Object Tracking and Segmentation: A Unifying Approach

Qiang Wang (Oxford):

Li Zhang (University of Oxford)*: http://pages.cs.wisc.edu/~lizhang/

Luca Bertinetto (University of Oxford):

Weiming Hu (Institute of Automation,Chinese Academy of Sciences): http://people.ucas.ac.cn/~huweiming

Philip Torr (University of Oxford): http://www.robots.ox.ac.uk/~tvg/

【Object tracking】Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters

Ugur Kart (Tampere University of Technology)*:

Alan Lukezic (University of Ljubljana):

Matej Kristan (University of Ljubljana):

Joni-Kristian Kamarainen (Tampere University):

Jiri Matas (CMP CTU FEE):

【Object tracking】Leveraging Shape Completion for 3D Siamese Tracking

Silvio Giancola (KAUST)*:

Jesus Zarzar (KAUST):

Bernard Ghanem (KAUST): http://www.bernardghanem.com/

【Object tracking】Target-Aware Deep Tracking

Xin Li (Harbin Institute of Technology, Shenzhen):

Chao Ma (Shanghai Jiao Tong University):

Baoyuan Wu (Tencent AI Lab):

Zhenyu He (Harbin Institute of Technology (Shenzhen))*:

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Object tracking】SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking

Guangting Wang (University of Science and Technology of China):

Chong Luo (Microsoft Research Asia)*:

Zhiwei Xiong (University of Science and Technology of China):

Wenjun Zeng (Microsoft Research):

【Object tracking】Siam RPN++: Evolution of Siamese Visual Tracking with Very Deep Networks

Bo Li (Sense Time Group Limited)*:

Wei Wu (Sense Time Group Limited):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

Qiang Wang (University of Chinese Academy of Sciences):

Fangyi Zhang (Institue of Computing Technology):

Junliang Xing (Institute of Automation, Chinese Academy of Sciences):

【Object tracking】La SOT: A High-quality Benchmark for Large-scale Single Object Tracking

Heng Fan (Temple University):

Liting Lin (South China University of Technology):

Fan Yang (Temple University):

Peng Chu (Temple University):

Ge Deng (Temple University):

Sijia Yu (Temple University):

Hexin Bai (Temple University):

Yong Xu (South China University of Technology):

Chunyuan Liao (Hiscene Technology):

Haibin Ling (Temple University)*: http://www.dabi.temple.edu/~hbling/

【Object tracking】Learning Independent Object Motion from Unlabelled Stereoscopic Videos

Zhe Cao (UC Berkeley)*:

Abhishek Kar (Fyusion Inc.):

Christian Haene (UC Berkeley):

Jitendra Malik (University of California at Berkley): http://www.cs.berkeley.edu/~malik/

【Object tracking】Deeper and Wider Siamese Networks for Real-Time Visual Tracking

Zhipeng Zhang (Chinese Academy of Sciences):

Houwen Peng (Microsoft Research)*:

【Object tracking】High Fidelity Facial Performance Tracking In-the-wild

Jae Shin Yoon (University of Minnestoa)*:

Takaaki Shiratori (Facebook Reality Labs):

Shoou-I Yu (Oculus Research Pittsburgh):

Hyun Soo Park (The University of Minnesota):

【Object tracking】Efficient Online Multi-Person 2D Pose Tracking with Recurrent Spatio-Temporal Affinity Fields

Yaadhav Raaj (CMU)*:

Haroon Idrees (Carnegie Mellon University):

Gines Hidalgo Martinez (Carnegie Mellon University):

Yaser Sheikh (CMU): http://www.cs.cmu.edu/~yaser/

【Object tracking】Eliminating Exposure Bias and Loss-Evaluation Mismatch in Multiple Object Tracking

Pascal Fua (EPFL, Switzerland): http://cvlabwww.epfl.ch/~fua/

Andrii Maksai (EPFL)*:

【Object tracking】Graph Convolutional Tracking

Junyu Gao (National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences)*:

Tianzhu Zhang (CAS, China):

Changsheng Xu (CASIA):

【Object tracking】ATOM: Accurate Tracking by Overlap Maximization

Martin Danelljan (ETH Zurich)*:

Goutam Bhat (ETH Zurich):

Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence):

Michael Felsberg (Linköping University): http://users.isy.liu.se/cvl/mfe/

【Object tracking】Visual Tracking via Adaptive Spatially-Regularized Correlation Filters

Kenan Dai (Dalian University of Technology):

Dong Wang (Dalian University of Technology)*:

Huchuan Lu (Dalian University of Technology): http://ice.dlut.edu.cn/lu/index.html

Chong Sun (Dalian University of Technology):

Jianhua Li (Dalian University of Technology):

【Object tracking】ROI Pooled Correlation Filters for Visual Tracking

Yuxuan Sun (Dalian University of Technology)*:

Chong Sun (Tencent Youtu Lab):

Dong Wang (Dalian University of Technology):

Huchuan Lu (Dalian University of Technology): http://ice.dlut.edu.cn/lu/index.html

You He (Naval Aviation University):

【Object tracking】MOTS: Multi-Object Tracking and Segmentation

Paul Voigtlaender (RWTH Aachen University)*:

Michael Krause (RWTH Aachen University):

Aljosa Osep (RWTH Aachen University):

Jonathon Luiten (RWTH Aachen University):

Berin Balachandar Gnana Sekar (RWTH Aachen University):

Andreas Geiger (MPI-IS and University of Tuebingen):

Bastian Leibe (RWTH Aachen University-): http://www.vision.rwth-aachen.de/

【Object tracking】Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking

Heng Fan (Temple University):

Haibin Ling (Temple University)*: http://www.dabi.temple.edu/~hbling/

【Object tracking】Know Before You Go: 3D Tracking and Forecasting with Rich Maps

John W Lambert (Georgia Institute of Technology)*:

James Hays (Georgia Institute of Technology, USA): http://www.cs.brown.edu/~hays/

Jagjeet Singh (CMU):

Ming Fang Chang (Carnegie Mellon University):

Simon Lucey (CMU): http://www.cs.cmu.edu/~slucey/

Deva Ramanan (Carnegie Mellon University): http://www.ics.uci.edu/~dramanan/

Patsorn Sangkloy (Georgia Institute of Technology):

De Wang (Argo AI):

Pete Carr (Argo AI):

【Object tracking】City Flow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

ZHENG TANG (University of Washington)*:

Milind Naphade (NVidia):

Ming-Yu Liu (NVIDIA):

Xiaodong Yang (NVIDIA Research):

Stan Birchfield (NVIDIA):

Shuo Wang (NVidia):

Ratnesh Kumar (NVIDIA):

David Anastasiu (SJSU):

Jenq-Neng Hwang (University of WA�):

【Object tracking】VITAMIN-E: VIsual Tracking And Mapp INg with Extremely Dense Feature Points

Masashi Yokozuka (National Institute of Advanced Industrial Science and Technology (AIST))*:

Shuji Oishi (National Institute of Advanced Industrial Science and Technology (AIST)):

Simon Thompson (AIST):

Atsuhiko Banno (AIST):

【Object tracking】Generalizing Eye Tracking with Bayesian Adversarial Learning

Kang Wang (RPI)*:

Rui Zhao (Rensselaer Polytechnic Institute):

Hui Su (IBM):

Qiang Ji (Rensselaer Polytechnic Institute): http://www.ecse.rpi.edu/~qji/

【Object tracking】Motion estimation of non-holonomic ground vehicles from a single feature correspondence measured over n views

Kun Huang (Shanghai Tech University)*:

Yifu Wang (Australian National University):

Laurent Kneip (Shanghai Tech University):

【Action recognition】Timeception for Complex Action Recognition

Noureldien Hussein (University of Amsterdam)*:

Stratis Gavves (University of Amsterdam):

Arnold W.M. Smeulders (University of Amsterdam):

【Action recognition】STEP: Spatio-Temporal Progressive Learning for Video Action Detection

Xitong Yang (University of Maryland)*:

Xiaodong Yang (NVIDIA Research):

Ming-Yu Liu (NVIDIA):

Fanyi Xiao (University of California Davis):

Larry Davis (University of Maryland): http://www.umiacs.umd.edu/~lsd/

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【Action recognition】Relational Action Forecasting

Chen Sun (Google)*:

Abhinav Shrivastava (University of Maryland):

Carl Vondrick (Columbia University):

Rahul Sukthankar (Google):

Kevin Murphy (Google):

Cordelia Schmid (Google): http://lear.inrialpes.fr/~schmid/

【Action recognition】What and How Well You Performed? A Multitask Approach To Action Quality Assessment

Paritosh Parmar (UNLV)*:

Brendan Morris (UNLV):

【Action recognition】Language-driven Temporal Activity Localization: A Semantic Matching Reinforcement Learning Model

Weining Wang (Institute of Automation, Chinese Academy of Sciences)*:

Yan Huang (Institute of Automation, Chinese Academy of Sciences):

Liang Wang (NLPR, China):

【Action recognition】Gaussian Temporal Awareness Networks for Action Localization

Fuchen Long (University of Science and Technology of China):

Ting Yao (JD AI Research)*:

Zhaofan Qiu (University of Science and Technology of China):

Xinmei Tian (USTC):

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

Tao Mei (AI Research of JD.com):

【Action recognition】A Perceptual Prediction Framework for Self Supervised Event Segmentation

Sathyanarayanan N Aakur (University of South Florida)*:

Sudeep Sarkar (University of South Florida, Tampa):

【Action recognition】An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition

Chenyang Si (Institute of Automation, Chinese Academy of Sciences)*:

Wentao Chen (CASIA):

Wei Wang (Institute of Automation Chinese Academy of Sciences):

Liang Wang (NLPR, China):

Tieniu Tan (NLPR, China): http://lab.datatang.com/1984DA173065/Default.aspx

【Action recognition】Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection

Jia-Xing Zhong (School of Electronic and Computer Engineering, Peking University):

Nannan Li (Peking University Shenzhen Graduate School):

Weijie Kong (School Electronic and Computer Engineering, Peking University):

Shan Liu (Tencent America):

Thomas H Li (Advanced Institute of Information Technology, Peking University):

Ge Li (SECE, Shenzhen Graduate School, Peking University)*:

【Action recognition】DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition

Zheng Shou (Columbia University):

Zhicheng Yan (Facebook AI)*:

Yannis Kalantidis (Facebook Research):

Laura Sevilla-Lara (Facebook):

Marcus Rohrbach (Facebook AI Research):

Xudong Lin (Columbia University):

Shih-Fu Chang (Columbia University): http://www.ee.columbia.edu/ln/dvmm/

【Action recognition】Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization

Daochang Liu (Peking University):

Tingting Jiang (Peking University)*:

Yizhou Wang (PKU):

【Action recognition】D3TW: Discriminative Differentiable Dynamic Time Warping for Weakly Supervised Action Alignment and Segmentation

Chien-Yi Chang (Stanford University)*:

De-An Huang (Stanford University):

Yanan Sui (Stanford University):

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

Juan Carlos Niebles (Stanford University): http://www.niebles.net/

【Action recognition】Progressive Teacher-student Learning for Early Action Prediction

Xionghui Wang (Sun Yat-sen University, China):

Jian-Fang HU (Sun Yat-sen University)*:

WEI-SHI ZHENG (Sun Yat-sen University, China):

Jianguo Zhang (University of Dundee):

Jian-Huang Lai (Sun Yat-sen University):

【Action recognition】MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation

Yazan Abu Farha (University of Bonn)*:

Jürgen Gall (University of Bonn):

【Action recognition】Transferable Interactiveness Prior for Human-Object Interaction Detection

Yong-Lu Li (Shanghai Jiao Tong University):

Siyuan Zhou (Shanghai Jiao Tong University):

Xijie Huang (Shanghai Jiao Tong University):

Liang Xu (Shanghai Jiao Tong University):

Ze Ma (SJTU):

Hao-Shu Fang (SJTU):

Yan-Feng Wang (Cooperative medianet innovation center of Shanghai Jiao Tong University):

Cewu Lu (Shanghai Jiao Tong University)*: http://mvig.sjtu.edu.cn/

【Action recognition】Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition

Maosen Li (Cooperative Medianet Innovation Center, Shang hai Jiao Tong University)*:

Siheng Chen (Carnegie Mellon University):

Xu Chen (Cooperative Medianet Innovation Center, Shanghai Jiaotong University):

Ya Zhang (Cooperative Medianet Innovation Center, Shang hai Jiao Tong University):

Yan-Feng Wang (Cooperative medianet innovation center of Shanghai Jiao Tong University):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Action recognition】Multi-granularity Generator for Temporal Action Proposal

yuan liu (Southeast University)*:

Lin Ma (Tencent AI Lab):

Yifeng Zhang (Southeast University):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Shih-Fu Chang (Columbia University): http://www.ee.columbia.edu/ln/dvmm/

【Action recognition】Peeking into the future: Predicting Future Person Activities and Locations in Videos

Junwei Liang (Carnegie Mellon University)*:

Lu Jiang (Google):

Juan Carlos Niebles (Stanford University): http://www.niebles.net/

Alexander Hauptmann (Carnegie Mellon University):

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

【Action recognition】Synthesizing Environment-Aware Activities via Activity Sketches

Yuan-Hong Liao (National Tsing Hua University)*:

Sanja Fidler (University of Toronto):

Antonio Torralba (MIT): http://web.mit.edu/torralba/www/

Xavier Puig (MIT):

Marko Boben (University of Ljubljana):

【Action recognition】EV-Gait: Event-based Robust Gait Recognition using Dynamic Vision Sensors

Yanxiang Wang (Harbin Engineering University):

Yiran Shen (Data61, CSIRO)*:

Bowen Du (University of Warwick):

Kai Wu (Fudan University):

Guangrong Zhao (Harbin Engineering University):

Jianguo Sun (Harbin Engineering University):

Hongkai Wen (University of Warwick):

【Action recognition】Bayesian Hierarchical Dynamic Model for Human Action Recognition

Rui Zhao (RPI)*:

Wanru Xu (Beijing Jiaotong University):

Hui Su (IBM):

Qiang Ji (Rensselaer Polytechnic Institute): http://www.ecse.rpi.edu/~qji/

【Action recognition】Mixed Effects Convolutional Neural Networks

Yunyang Xiong (University of Wisconsin-Madison)*:

Hyunwoo J Kim (Korea University):

Vikas Singh (University of Wisconsin-Madison USA): http://www.biostat.wisc.edu/~vsingh/

【Action recognition】3D human pose estimation in video with temporal convolutions and semi-supervised training

Dario Pavllo (Facebook)*:

Christoph Feichtenhofer (Facebook AI Research):

David Grangier (Google):

Michael Auli (Facebook):

【Action recognition】Pose Fix: Model-agnostic General Human Pose Refinement Network

Gyeongsik Moon (Seoul National University):

Ju Yong Chang (Kwangwoon University):

Kyoung Mu Lee (Seoul National University)*: http://cv.snu.ac.kr/kmlee/

【Action recognition】Rep Net: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation

Bastian Wandt (Leibniz University Hannover)*:

Bodo Rosenhahn (Leibniz University Hannover):

【Action recognition】Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views

Junting Dong (Zhejiang University):

Wen Jiang (Zhejiang University):

Qixing Huang (The University of Texas at Austin):

Hujun Bao (Zhejiang University):

Xiaowei Zhou (Zhejiang Univ., China)*:

【Action recognition】Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video

Radu Tudor Ionescu (University of Bucharest)*:

Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence):

Mariana-Iuliana Georgescu (University of Bucharest):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Action recognition】DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition

Toby Perrett (University of Bristol):

Dima Damen (University of Bristol)*:

【Action recognition】Collaborative Spatiotemporal Feature Learning for Video Action Recognition

Chao Li (Hikvision Research Institute):

Qiaoyong Zhong (Hikvision Research Institute):

Di Xie (Hikvision Research Institute)*:

Shiliang Pu (Hikvision Research Institute):

【Action recognition】MARS: Motion-Augmented RGB Stream for Action Recognition

Nieves Crasto (INRIA)*:

Philippe Weinzaepfel (Naver Labs Europe):

Karteek Alahari (Inria):

Cordelia Schmid (INRIA): http://lear.inrialpes.fr/~schmid/

【Action recognition】Convolutional Relational Machine for Group Activity Recognition

Sina Mokhtarzadeh Azar (Amirkabir University of Technology):

Mina Ghadimi Atigh (Amirkabir University of Technology):

Ahmad Nickabadi (Amirkabir University of Technology )*:

Alexandre Alahi (EPFL):

【Action recognition】Skeleton-Based Action Recognition with Directed Graph Neural Networks

Lei Shi (Institute of Automation,Chinese Academy of Sciences )*:

Yifan o Zhang (Institute of Automation, Chinese Academy of Sciences):

Jian Cheng (“Chinese Academy of Sciences, China”): http://www.nlpr.ia.ac.cn/jcheng/

Hanqing Lu (NLPR, Institute of Automation, CAS): http://people.ucas.ac.cn/~luhanqing

【Action recognition】Deep Dual Relation Modeling for Egocentric Interaction Recognition

Haoxin Li (Sun Yat-sen University)*:

Yijun Cai (Sun Yat-sen University):

WEI-SHI ZHENG (Sun Yat-sen University, China):

【Action recognition】Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning

Rohit Pandey (Google)*:

Anastasia Tkach (Google):

Shuoran Yang (Google):

Pavel Pidlypenskyi (Google):

Jonathan Taylor (Google Inc.):

Ricardo Martin-Brualla (Google):

Andrea Tagliasacchi (Google Inc.):

George Papandreou (Google): http://www.stat.ucla.edu/~gpapan/index.html

Philip Davidson (Google Inc.):

Cem Keskin (Google):

Shahram Izadi (Google):

Sean Fanello (Google):

【Action recognition】Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network

Chen Li (National University of Singapore)*:

Gim Hee Lee (National University of SIngapore): https://sites.google.com/site/gimheelee/home/publications

【Action recognition】Cross Info Net: Multi-Task Information Sharing Based Hand Pose Estimation

Kuo Du (Dalian University of Technology):

Xiangbo Lin (Dalian University of Technology)*:

Yi Sun (Dalian University of Technology):

Xiaohong Ma (Dalian University of Technology):

【Action recognition】Action Recognition from Single Timestamp Supervision in Untrimmed Videos

Davide Moltisanti (University of Bristol)*:

Sanja Fidler (University of Toronto):

Dima Damen (University of Bristol):

【Action recognition】Time-Conditioned Action Anticipation in One Shot

Qiuhong Ke (MPI)*:

Mario Fritz (CISPA Helmholtz Center for Information Security): https://scalable.mpi-inf.mpg.de/

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

【Action recognition】Dance with Flow: Two-in-One Stream Action Detection

JIAOJIAO ZHAO (University of Amsterdam)*:

Cees Snoek (University of Amsterdam):

【Action recognition】Representation Flow for Action Recognition

AJ Piergiovanni (Indiana University)*:

Michael S Ryoo (Google Brain:

Indiana University):

【Action recognition】LSTA: Long Short-Term Attention for Egocentric Action Recognition

Swathikiran Sudhakaran (Fondazione Bruno Kessler, Italy)*:

Sergio Escalera (Computer Vision Center (UAB) & University of Barcelona,): http://sergioescalera.com/

Oswald Lanz (Fondazione Bruno Kessler, Italy):

【Action recognition】Learning Actor Relation Graphs for Group Activity Recognition

Jianchao Wu (Nanjing University ):

Limin Wang (Nanjing University)*: http://wanglimin.github.io/

Li Wang (Nan Jing University):

Jie Guo (Nanjing University):

Gangshan Wu (Nanjing University):

【Action recognition】A Structured Model For Action Detection

Yubo Zhang (Carnegie Mellon University)*:

Pavel Tokmakov (CMU):

Cordelia Schmid (INRIA): http://lear.inrialpes.fr/~schmid/

Martial Hebert (Carnegie Mellon School of Computer Science): http://www.cs.cmu.edu/~hebert/

【Action recognition】Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition

Devraj Mandal (Indian Institute of Science, Bangalore):

Sanath Narayan (Inception Institute of Artificial Intelligence)*:

Sai Kumar Dwivedi (Mercedes Benz Research and Development India):

vikram gupta (MBRDI):

Shuaib Ahmed (Mercedes-Benz R&D India):

Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Action recognition】Towards Natural and Accurate Future Motion Prediction of Humans and Animals

Zhenguang Liu (Zhejiang Gongshang University)*:

Shuang Wu (Nanyang Technological University):

Shuyuan Jin (NUS):

Qi Liu (National University of Singapore):

Shijian Lu (Nanyang Technological University):

Roger Zimmermann (NUS):

Li Cheng (University of Alberta):

【Action recognition】Local Features and Visual Words Emerge in Activations

Oriane Siméoni (Inria)*:

Yannis Avrithis (Inria):

Ondrej Chum (Vision Recognition Group, Czech Technical University in Prague): http://cmp.felk.cvut.cz/~chum/

【Action recognition】Learning joint reconstruction of hands and manipulated objects

Yana Hasson (Inria)*:

Gul Varol (INRIA):

Dimitrios Tzionas (Max Planck Institute for Intelligent Systems):

Igor Kalevatykh (INRIA Paris):

Michael J. Black (Max Planck Institute for Intelligent Systems): http://ps.is.tue.mpg.de/person/black

Ivan Laptev (INRIA Paris): http://www.di.ens.fr/~laptev/index.html

Cordelia Schmid (INRIA): http://lear.inrialpes.fr/~schmid/

【Action recognition】Action4D: Online Action Recognition in the Crowd and Clutter

Quanzeng You (Microsoft):

Hao Jiang (Microsoft)*:

【Action recognition】3D Hand Shape and Pose Estimation from a Single RGB Image

Liuhao Ge (Nanyang Technological University)*:

Zhou Ren (Snap Inc.):

Yuncheng Li (Snap):

Zehao Xue (Snap Inc.):

Yingying Wang (Snap Inc.):

Jianfei Cai (Nanyang Technological University): http://www3.ntu.edu.sg/home/asjfcai/

Junsong Yuan (“State University of New York at Buffalo, USA”): https://cse.buffalo.edu/~jsyuan/

【Action recognition】3D hand shape and pose from images in the wild

Adnane Boukhayma (University of Oxford)*:

Rodrigo de Bem (University of Oxford):

Philip Torr (University of Oxford): http://www.robots.ox.ac.uk/~tvg/

【Action recognition】Self supervised 3D hand pose estimation

Chengde Wan (ETHZ)*:

Thomas Probst (ETH Zurich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

Angela Yao (National University of Singapore):

【Action recognition】Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation

Xipeng Chen (Sun Yat-sen University):

Kwan-Yee Lin (Peking university):

Wentao Liu (Sensetime):

Chen Qian (Sense Time):

Liang Lin (Sun Yat-sen University)*: http://ss.sysu.edu.cn/~ll/index.html

【Action recognition】In the Wild Human Pose Estimation using Explicit 2D Features and Intermediate 3D Representations

Ikhsanul Habibie (Max Planck Institute for Informatics)*:

Weipeng Xu (MPII):

Dushyant Mehta (MPI Informatics):

Gerard Pons-Moll (MPII, Germany): https://ps.is.tuebingen.mpg.de/person/gpons

Christian Theobalt (MPI Informatik):

【Action recognition】Monocular Total Capture: Posing Face, Body, and Hands in the Wild

Donglai Xiang (Carnegie Mellon University)*:

Hanbyul Joo (CMU):

Yaser Sheikh (CMU): http://www.cs.cmu.edu/~yaser/

【Action recognition】Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer

Shile Li (Technical University of Munich)*:

Dongheui Lee (Technical University of Munich):

【Action recognition】Improving User-Specific Gaze Estimation via Gaze Redirection Synthesis

Yu Yu (Idiap, and EPFL)*:

Gang Liu (Idiap Research Institute):

Jean-Marc ODOBEZ (IDIAP/EPFL, SWITZERLAND):

【Action recognition】TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection

Lin Song (Xi’an Jiaotong University)*:

Shiwei Zhang (Huazhong University of Science and Technology):

Gang Yu (Face++):

Hongbin Sun (Xi’an Jiaotong University):

【Action recognition】Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

Romero Morais (Deakin University)*:

Vuong Le (Deakin University):

Budhaditya Saha (Deakin University):

Truyen Tran (Deakin University):

Moussa Reda Mansour (i Cetana):

Svetha Venkatesh (Deakin University):

【Action recognition】Local Temporal Bilinear Pooling for Fine-grained Action Parsing

Yan Zhang (Institute of Neural Information Processing, Ulm University)*:

Siyu Tang (MPI for Intelligent Systems):

Krikamol Muandet (Max Planck Institute for Intelligent Systems):

Christian Jarvers (Ulm University):

Heiko Neumann (Ulm University):

【Action recognition】Improving Action Localization by Progressive Cross-stream Cooperation

RUI SU (the University of Sydney):

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Luping Zhou (University of Sydney):

Dong Xu (University of Sydney)*: http://www.ntu.edu.sg/home/dongxu/

【Action recognition】Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

Lei Shi (Institute of Automation,Chinese Academy of Sciences )*:

Yifan o Zhang (Institute of Automation, Chinese Academy of Sciences):

Jian Cheng (“Chinese Academy of Sciences, China”): http://www.nlpr.ia.ac.cn/jcheng/

Hanqing Lu (NLPR, Institute of Automation, CAS): http://people.ucas.ac.cn/~luhanqing

【Action recognition】A neural network based on SPD manifold learning for skeleton-based hand gesture recognition

Xuan Son Nguyen (Ensicaen)*:

luc brun (GREYC-ENSICAEN):

Olivier Lézoray (University of Caen Nodmandy):

Sébastien Bougleux (Normadie Univ, UNICAEN, ENSICAEN, CNRS, GREYC):

【Action recognition】Large-scale weakly-supervised pre-training for video action recognition

Dhruv Mahajan (Facebook):

Deepti Ghadiyaram (Facebook)*:

Du Tran (Facebook Research):

【Action recognition】Unsupervised learning of action classes with continuous temporal embedding

Anna Kukleva (University of Bonn):

Hilde Kuehne (University of Bonn)*:

Fadime Sener (University of Bonn):

Jürgen Gall (University of Bonn):

【Action recognition】SR-LSTM: State Refinement for LSTM towards Pedestrian Trajectory Prediction

Pu Zhang (Xi’an Jiaotong University):

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Pengfei Zhang (Xi’an Jiaotong University):

Jianru Xue (Xi’an Jiaotong University)*:

Nanning Zheng (Xi’an Jiaotong University):

【Video analysis】Deep RNN Framework for Visual Sequential Applications

Bo Pang (Shanghai Jiao Tong University):

Kaiwen Zha (Shanghai Jiao Tong University):

Hanwen Cao (Shanghai Jiao Tong University):

Chen Shi (Shanghai Jiao Tong University):

Cewu Lu (Shanghai Jiao Tong University)*: http://mvig.sjtu.edu.cn/

【Video analysis】Video Action Transformer Network

Rohit Girdhar (Carnegie Mellon University)*:

Joao Carreira (Deep Mind):

Carl Doersch (Deep Mind):

Andrew Zisserman (University of Oxford): http://www.robots.ox.ac.uk/~vgg/

【Video analysis】Long-Term Feature Banks for Detailed Video Understanding

Chao-Yuan Wu (UT Austin)*:

Christoph Feichtenhofer (Facebook AI Research):

Haoqi Fan (Facebook AI Research):

Kaiming He (Facebook AI Research): http://research.microsoft.com/en-us/um/people/kahe/

Philipp Kraehenbuehl (UT Austin): https://www.philkr.net/

Ross Girshick (FAIR): http://www.cs.berkeley.edu/~rbg/

【Video analysis】Efficient Video Classification Using Fewer Frames

Shweta Bhardwaj (Indian Institute of Technology Madras, Chennai)*:

Mukundhan Srinivasan (NVIDIA):

Mitesh M. Khapra (Indian Institute of Technology Madras):

【Video analysis】COIN: A Large-scale Dataset for Comprehensive Instruction Video Analysis

Yansong Tang (Tsinghua University):

Dajun Ding (Meitu, Inc.):

Yongming Rao (Tsinghua University):

Yu Zheng (Tsinghua University):

Danyang Zhang (Tsinghua University):

Lili Zhao (Meitu):

Jiwen Lu (Tsinghua University)*:

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【Video analysis】Less is More: Learning Highlight Detection from Video Duration

Bo Xiong (University of Texas at Austin)*:

Yannis Kalantidis (Facebook Research):

Deepti Ghadiyaram (Facebook):

Kristen Grauman (Facebook AI Research & UT Austin): http://www.cs.utexas.edu/~grauman/

【Video analysis】Ada Frame: Adaptive Frame Selection for Fast Video Recognition

Zuxuan Wu (UMD)*:

Caiming Xiong (Salesforce Research):

Chih-Yao Ma (Georgia Institute of Technology):

Richard Socher (Salesforce):

Larry Davis (University of Maryland): http://www.umiacs.umd.edu/~lsd/

【Video analysis】GIF2Video: Color Dequantization and Temporal Interpolation of GIF images

Yang Wang (Stony Brook University)*:

Haibin Huang (Face++ (Megvii)):

Chuan Wang (Face++ (Megvii)):

Tong He (UCLA):

jue wang (Face++ (Megvii)):

Minh Hoai Nguyen (Stony Brook University): http://www3.cs.stonybrook.edu/~minhhoai/

【Video analysis】Social Relation Recognition from Videos via Multi-scale Spatial-Temporal Reasoning

Xinchen Liu (JD.com)*:

Wu Liu (AI Research of JD.com):

Meng Zhang (Beijing University of Posts and Telecommunications):

Jingwen Chen (Hangzhou Dianzi University):

Lianli Gao (The University of Electronic Science and Technology of China):

Chenggang Yan (Hangzhou Dianzi University):

Tao Mei (JD.com):

【Video analysis】IM-Net for High Resolution Video Frame Interpolation

Tomer Peleg (Samsung Israel R&D Center)*:

Pablo Szekely (Samsung Israel R&D Center):

Doron Sabo (Samsung Israel R&D Center):

Omry Sendik (Samsung Israel R&D Center):

【Video analysis】The Visual Centrifuge: Model-Free Layered Video Representations

Jean-Baptiste Alayrac (Deep Mind):

Joao Carreira (Deep Mind)*:

Andrew Zisserman (University of Oxford): http://www.robots.ox.ac.uk/~vgg/

【Video analysis】Depth-Aware Video Frame Interpolation

Wenbo Bao (Shanghai Jiao Tong University)*:

Wei-Sheng Lai (University of California, Merced):

Chao Ma (Shanghai Jiao Tong University):

Xiaoyun Zhang (Shanghai Jiao Tong University):

Zhiyong Gao (Shanghai Jiao Tong University):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Video analysis】Robust Video Stabilization by Optimization in CNN Weight Space

Jiyang Yu (University of California San Diego)*:

Ravi Ramamoorthi (University of California San Diego):

【Video analysis】Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics

Jiangliu WANG (CUHK):

Jianbo Jiao (University of Oxford):

Linchao Bao (Tencent AI Lab)*:

Shengfeng He (South China University of Technology):

Yunhui Liu (CUHK):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Video analysis】Towards Accurate Task Accomplishment with Low-Cost Robotic Arms

Yiming Zuo (Tsinghua University)*:

Weichao Qiu (Johns Hopkins University):

Lingxi Xie (Johns Hopkins University):

Fangwei Zhong (Peking University):

Yizhou Wang (PKU):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Video analysis】Learning to Film from Professional Human Motion Videos

Chong Huang (UC Santa Barbara):

Chuan-en Lin (Hong Kong University of Science and Technology):

Zhenyu Yang (UC Santa Barbara):

Yan Kong (UC Santa Barbara):

Peng Chen (Zhejiang University of Technology):

Xin Yang (Huazhong University of Science and Technology)*:

Kwang-Ting Cheng (Hong Kong University of Science and Technology):

【Video analysis】Learning Video Representations from Correspondence Proposals

Xingyu Liu (Stanford University)*:

Joon-Young Lee (Adobe Research):

Hailin Jin (Adobe Research): http://vision.ucla.edu/~hljin/

【Video analysis】Rethinking the Evaluation of Video Summaries

Mayu Otani (Cyber Agent, Inc.)*:

Yuta Nakashima (Osaka University):

Esa Rahtu (Tampere University of Technology):

Janne Heikkila (University of Oulu, Finland):

【Video analysis】Face-Focused Cross-Stream Network for Deception Detection in Videos

Mingyu Ding (Renmin University of China):

An Zhao (Renmin University of China):

Zhiwu Lu (Renmin University of China)*:

Tao Xiang (University of Surrey):

Ji-Rong Wen (Renmin University of China):

【Video analysis】The Pros and Cons: Rank-aware Temporal Attention for Skill Determination in Long Videos

Hazel Doughty (University of Bristol)*:

Walterio Mayol-Cuevas (Bristol University):

Dima Damen (University of Bristol):

【Video analysis】Video Summarization by Learning from Unpaired Data

Mrigank Rochan (University of Manitoba)*:

Yang Wang (University of Manitoba):

【Video analysis】PA3D: Pose-Action 3D Machine for Video Recognition

An Yan (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Yali Wang (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Zhifeng Li (Tencent AI Lab):

Yu Qiao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)*: http://mmlab.siat.ac.cn/yuqiao/

【Video analysis】Grounded Video Description

Luowei Zhou (University of Michigan)*:

Yannis Kalantidis (Facebook Research):

Xinlei Chen (Facebook AI Research):

Jason J Corso (University of Michigan):

Marcus Rohrbach (Facebook AI Research):

【Video analysis】Inserting Videos into Videos

Donghoon Lee (Seoul National University)*:

Tomas Pfister (Google):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Video analysis】Viewport Proposal CNN for 360° Video Quality Assessment

Chen Li (BUAA):

Mai Xu (BUAA)*:

Lai Jiang (BUAA):

Shanyi Zhang (BUAA):

Xiaoming Tao (Tsinghua University):

【Video analysis】Self-supervised Spatiotemporal Learning via Video Clip Order Prediction

Dejing Xu (Zhejiang University)*:

Jun Xiao (Zhejiang University):

Zhou Zhao (Zhejiang University):

Jian Shao (Zhejiang University):

Di Xie (Hikvision Research Institute):

Yueting Zhuang (Zhejiang University):

【Video analysis】Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph

Yao-Hung Tsai (Carnegie Mellon University)*:

Santosh Divvala (Allen Institute for AI): http://homes.cs.washington.edu/~santosh/

Louis-Philippe Morency (Carnegie Mellon University):

Ruslan Salakhutdinov (Carnegie Mellon University): http://www.cs.toronto.edu/~rsalakhu/

Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence): http://homes.cs.washington.edu/~ali/index.html

【Video analysis】Not All Frames Are Equal: Weakly-Supervised Video Grounding with Contextual Similarity and Visual Clustering Losses

Jing Shi (University of Rochester)*:

Jia Xu (Tencent AI Lab):

Boqing Gong (Tencent AI Lab):

Chenliang Xu (University of Rochester): http://www.cs.rochester.edu/~cxu22/

【Video analysis】Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration

De-An Huang (Stanford University)*:

Suraj Nair (Stanford University):

Danfei Xu (Stanford University):

Yuke Zhu (Stanford University):

Animesh Garg (Stanford University):

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

Juan Carlos Niebles (Stanford University): http://www.niebles.net/

【Video analysis】Multimodal Explanations by Predicting Counterfactuality in Videos

Atsushi Kanehira (The University of Tokyo)*:

Kentaro Takemoto (University of Tokyo):

Sho Inayoshi (The University of Tokyo):

Tatsuya Harada (The University of Tokyo):

【Video analysis】Estimating 3D Motion and Forces of Person-Object Interactions from Monocular Video

Zongmian Li (INRIA Paris)*:

Jiri Sedlar (CVUT):

Justin Carpentier (INRIA):

Ivan Laptev (INRIA Paris): http://www.di.ens.fr/~laptev/index.html

Nicolas Mansard (LAAS-CNRS):

Josef Sivic (INRIA):

【Video analysis】Learning Spatio-Temporal Representation with Local and Global Diffusion

Zhaofan Qiu (University of Science and Technology of China):

Ting Yao (JD AI Research)*:

Chong-Wah Ngo (City University of Hong Kong):

Xinmei Tian (USTC):

Tao Mei (AI Research of JD.com):

【Video analysis】Zoom-In-to-Check: Boosting Video Interpolation via Instance-level Discrimination

Liangzhe Yuan (University of Pennsylvania)*:

Yibo Chen (University of Pennsylvania):

Hantian Liu (University of Pennsylvania):

Tao Kong (Tsinghua):

Jianbo Shi (University of Pennsylvania): http://www.cis.upenn.edu/~jshi/

【Video analysis】Neural RGB -> D Sensing: Depth and Uncertainty from a Video Camera

Chao Liu (Carnegie Mellon University):

Jinwei Gu (NVIDIA)*:

Kihwan Kim (NVIDIA):

Srinivasa G Narasimhan (Carnegie Mellon University):

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【Video analysis】Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping

Suhas Lohit (Arizona State University)*:

Qiao Wang (Arizona State University):

Pavan Turaga (Arizona State University):

【Video analysis】Dynamics are Important for the Recognition of Equine Pain in Video

Sofia Broomé (KTH Royal Institute of Technology)*:

Karina Bech Gleerup (University of Copenhagen):

Pia Haubro Andersen (Swedish University of Agricultural Sciences):

Hedvig Kjellström (KTH Royal Institute of Technology):

【Human detection】Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification

Yifan Sun (Tsinghua University):

Ya-Li Li (THU):

Qin Xu (Tsinghua University):

Chi Zhang (Megvii Inc.):

Yikang Li (CUHK):

Shengjin Wang (Tsinghua University)*:

Jian Sun (Megvii Technology): http://research.microsoft.com/en-us/groups/vc/

【Human detection】Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification

Zhun Zhong (Xiamen University)*:

Liang Zheng (Australian National University):

Zhiming Luo (Xiamen University):

Shaozi Li (Xiamen University, China):

Yi Yang (UTS): http://www.cs.cmu.edu/~yiyang/

【Human detection】Dissecting Person Re-identification from the Viewpoint of Viewpoint

Xiaoxiao Sun (Singapore University of Technology and Design)*:

Liang Zheng (Australian National University):

【Human detection】Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identification

Zhixiang Wang (National Taiwan University):

Zheng Wang (National Institute of Informatics)*:

Yinqiang Zheng (National Institute of Informatics): https://researchmap.jp/yinqiangzheng

Yung-Yu Chuang (National Taiwan University):

Shin’ichi Satoh (National Institute of Informatics):

【Human detection】Densely Semantically Aligned Person Re-Identification

Zhizheng Zhang (University of Science and Technology of China):

Cuiling Lan (Microsoft Research)*:

Wenjun Zeng (Microsoft Research):

Zhibo Chen (University of Science and Technology of China):

【Human detection】Generalizable Person Re-identification by Domain-Invariant Mapping Network

Jifei Song (Queen Mary, University of London)*:

Yongxin Yang (University of Edinburgh ):

Yi-Zhe Song (Queen Mary University of London):

Tao Xiang (University of Surrey):

Timothy Hospedales (Edinburgh University): http://homepages.inf.ed.ac.uk/thospeda/

【Human detection】Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification

Song Bai (University of Oxford)*:

Peng Tang (Huazhong University of Science and Technology):

Longin Jan Latecki (Temple University):

Philip Torr (University of Oxford): http://www.robots.ox.ac.uk/~tvg/

【Human detection】Weakly Supervised Person Re-Identification

Jingke Meng (Sun Yat-Sun University):

Sheng Wu (Sen Yat-Sun University):

WEI-SHI ZHENG (Sun Yat-sen University, China)*:

【Human detection】Query-guided End-to-End Person Search

Bharti Munjal (OSRAM)*:

Sikandar Amin (OSRAM Gmb H):

Federico Tombari (Technical University of Munich, Germany): http://vision.deis.unibo.it/fede/

Fabio Galasso (OSRAM):

【Human detection】Distilled Person Re-identification: Towards a More Scalable System

Ancong Wu (Sun Yat-sen University):

WEI-SHI ZHENG (Sun Yat-sen University, China)*:

Xiaowei Guo (Tencent Youtu Lab):

Jian-Huang Lai (Sun Yat-sen University):

【Human detection】Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-Identification

Wenjie Yang (Institute of Automation, Chinese Academy of Sciences)*:

Houjing Huang (CASIA):

Zhang Zhang (Institute of Automation, Chinese Academy of Sciences):

Xiaotang Chen (Institute of Automation, Chinese Academy of Sciences):

Kaiqi Huang (Institute of Automation, Chinese Academy of Sciences):

Shu Zhang (Deepwise AI Lab):

【Human detection】Joint Discriminative and Generative Learning for Person Re-identification

Zhedong Zheng (University of Technology Sydney)*:

Xiaodong Yang (NVIDIA Research):

Zhiding Yu (NVIDIA):

Liang Zheng (Australian National University):

Yi Yang (University of Technology, Sydney): http://www.cs.cmu.edu/~yiyang/

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【Human detection】Unsupervised Person Re-identification by Soft Multilabel Learning

Hong-Xing Yu (Sun Yat-Sen University):

WEI-SHI ZHENG (Sun Yat-sen University, China)*:

Ancong Wu (Sun Yat-sen University):

Xiaowei Guo (Tencent Youtu Lab):

Shaogang Gong (Queen Mary University of London): http://www.eecs.qmul.ac.uk/~sgg/

Jian-Huang Lai (Sun Yat-sen University):

【Human detection】Learning Context Graph for Person Search

Yichao Yan (Shanghai Jiao Tong University)*:

Qiang Zhang (Shanghai Jiao Tong University):

Bingbing Ni (Shanghai Jiao Tong University):

Wendong Zhang (Shanghai Jiao Tong University):

Minghao Xu (Shanghai Jiaotong University):

Xiaokang Yang (Shanghai Jiao Tong University of China):

【Human detection】Learning Individual Styles of Conversational Gesture

Shiry Ginosar (UC Berkeley)*:

Amir Bar (Zebra Medical Vision):

Gefen Kohavi (UC Berkeley):

Caroline M Chan (MIT):

Andrew Owens (UC Berkeley):

Jitendra Malik (University of California at Berkley): http://www.cs.berkeley.edu/~malik/

【Human detection】Patch Based Discriminative Feature Learning for Unsupervised Person Re-identification

Qize Yang (Sun Yat-sen University):

Hong-Xing Yu (Sun Yat-Sen University):

Ancong Wu (Sun Yat-sen University):

WEI-SHI ZHENG (Sun Yat-sen University, China)*:

【Human detection】Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification

Yiru Zhao (Shanghai Jiao Tong University)*:

Xu Shen (Alibaba Group):

Zhongming Jin (Alibaba Group):

Hongtao Lu (Shanghai Jiao Tong University):

Xiansheng Hua (Damo Academy, Alibaba Group):

【Human detection】Learning to Learn Relation for Important People Detection in Still Images

Wei-Hong Li (University of Edinburgh):

Fa-Ting Hong (Sun Yat-Sen University):

WEI-SHI ZHENG (Sun Yat-sen University, China)*:

【Human detection】High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection

Wei Liu (National University of Defense Technology): http://www.ee.columbia.edu/~wliu/

Shengcai Liao (Inception Institute of Artificial Intelligence)*:

Weiqiang Ren (Horizon Robotics):

Weidong Hu (National University of Defence Technology):

Yinan Yu (Horizon Robotics):

【Human detection】Gait Recognition via Disentangled Representation Learning

Ziyuan Zhang (Michigan State University)*:

Luan Tran (Michigan State University):

Xi Yin (Microsoft Could & AI):

Yousef A Atoum (Yarmouk University):

Xiaoming Liu (Michigan State University):

Nanxin Wang (Ford Motor Company):

Jian Wan (Ford Motor Company):

【Human detection】AANet: Attribute Attentio Network for Person Re-Identification

Chiat Pin Tay (Nanyang Technological University)*:

Sharmili Roy (Nanyang Technological University):

Kim Yap (Nanyang Technological University):

【Human detection】Adaptive NMS: Refining Pedestrian Detection in a Crowd

Songtao Liu (BUAA):

Di Huang (Beihang University, China)*:

Yunhong Wang (State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China): http://irip.buaa.edu.cn/Chinese.html

【Human detection】VRSTC: Occlusion-Free Video Person Re-Identification

Ruibing Hou (Institute of Computing Technology,Chinese Academy):

Bingpeng MA (UCAS)*:

Hong Chang (Chinese Academy of Sciences):

Xinqian Gu (University of Chinese Academy of Sciences):

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

Xilin Chen (China):

【Human detection】Adaptive Transfer Network for Cross-Domain Person Re-Identification

Jiawei Liu (University of Science and Technology of China):

Zheng-Jun Zha (University of Science and Technology of China)*:

Di Chen (University of Science and Technology of China):

Richang Hong (He Fei University of Technology):

Meng Wang (Hefei University of Technology):

【Human detection】Pedestrian Detection with Autoregressive Network Phases

Garrick Brazil (Michigan State University)*:

Xiaoming Liu (Michigan State University):

【Human detection】Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training

Feng Zheng (Southern University of Science and Technology)*:

Rongrong Ji (Xiamen University, China):

Cheng Deng (Xidian University):

Xing Sun (Tencent):

Xinyang Jiang (Tencent):

Xiaowei Guo (Tencent Youtu Lab):

Zongqiao Yu (Tencent):

Feiyue Huang (Tencent):

【Human detection】Interaction-and-Aggregation Network for Person Re-identification

Ruibing Hou (Institute of Computing Technology,Chinese Academy):

Bingpeng MA (UCAS)*:

Hong Chang (Chinese Academy of Sciences):

Xinqian Gu (University of Chinese Academy of Sciences):

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

Xilin Chen (China):

【Human parsing】Parsing R-CNN for Instance-Level Human Analysis

Lu Yang (Beijing University of Posts and Telecommunications):

Qing Song (Beijing University of Posts and Telecommunications)*:

Zhihui Wang (Beijing University of Posts and Telecommunications):

Ming Jiang (Wi Wide Inc.):

【Human parsing】Pushing the Envelope for RGB-based Dense 3D Hand Pose Estimation via Neural Rendering

Seungryul Baek (Imperial College London)*:

Kwang In Kim (UNIST):

Tae-Kyun Kim (Imperial College London): https://labicvl.github.io/

【Human parsing】Self-Supervised Learning of 3D Human Pose using Multi-view Geometry

Muhammed Kocabas (Middle East Technical University)*:

Salih Karagoz (Middle East Technical University):

Emre Akbas (Middle East Technical University):

【Human parsing】FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image

Tsun-Yi Yang (Scape Technologies:

Academia Sinica, Taiwan:

National Taiwan University, Taiwan)*:

Yi-Ting Chen (Academia Sinica):

Yen-Yu Lin (Academia Sinica):

Yung-Yu Chuang (National Taiwan University):

【Human parsing】Dense 3D Face Decoding over 2500FPS: Joint Texture \& Shape Convolutional Mesh Decoders

Yuxiang Zhou (Imperial College London):

Jiankang Deng (Imperial College London)*:

Irene Kotsia (Hellenic Open University):

Stefanos Zafeiriou (Imperial College Londong):

【Human parsing】Does Learning Specific Features for Related Parts Help Human Pose Estimation?

Wei Tang (Northwestern University)*:

Ying Wu (Northwestern University):

【Human parsing】Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal Training

Mahdi Abavisani (Rutgers University)*:

HAMID VAEZI JOZE (Microsoft):

Vishal Patel (Johns Hopkins University):

【Human parsing】Learning to Reconstruct People in Clothing from a Single RGB Camera

Thiemo Alldieck (TU Braunschweig)*:

Marcus Magnor (TU Braunschweig):

Bharat Lal Bhatnagar (MPI-INF):

Christian Theobalt (MPI Informatik):

Gerard Pons-Moll (MPII, Germany): https://ps.is.tuebingen.mpg.de/person/gpons

【Human parsing】Layout-Graph Reasoning for Fashion Landmark Detection

Weijiang Yu (SUN YAT-SEN UNIVERSITY):

Xiaodan Liang (Sun Yat-sen University)*:

Ke Gong (Sun Yat-sen University ):

Chen Han Jiang (Sun Yat-sen University):

Nong Xiao (Sun Yat-sen University):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

【Human parsing】Exploiting temporal context for 3D human pose estimation in the wild

Anurag Arnab (University of Oxford)*:

Carl Doersch (Deep Mind):

Andrew Zisserman (University of Oxford): http://www.robots.ox.ac.uk/~vgg/

【Human parsing】Semantic Graph Convolutional Networks for 3D Human Pose Regression

Long Zhao (Rutgers University)*:

Xi Peng (Binghamton University):

Yu Tian (Rutgers):

Mubbasir Kapadia (Rutgers University):

Dimitris Metaxas (Rutgers):

【Human parsing】Fast Human Pose Estimation

Feng Zhang (University of Electronic Science and Technology of China):

Xiatian Zhu (Vision Semantics Limited):

Mao Ye (University of Electronic Science and Technology of China)*:

【Human parsing】Textured Neural Avatars

Aliaksandra Shysheya (Samsung):

Egor Zakharov (Skoltech):

Renat Bashirov (Samsung):

Igor Pasechnik (Samsung):

Egor Burkov (Skoltech):

Dmitry Ulyanov (Skoltech):

Yury Malkov (Samsung):

Karim Iskakov (Samsung):

Kara-Ali Aliev (Samsung):

Alexey Ivakhnenko (Samsung):

Alexander Vakhitov (Samsung AI Research Center):

Victor Lempitsky (Samsung)*:

【Human parsing】Dense Intrinsic Appearance Flow for Human Pose Transfer

Yining Li (Chinese University of Hong Kong)*:

Chen Huang (Carnegie Mellon University):

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

【Human parsing】Deep Fashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Retrieval of Clothing Images

Yuying Ge (The Chinese University of Hong Kong)*:

Ruimao Zhang (The Chinese University of Hong Kong):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Xiaoou Tang (The Chinese University of Hong Kong): http://mmlab.ie.cuhk.edu.hk/

Ping Luo (The Chinese University of Hong Kong):

【Human parsing】Simul Cap : Single-View Human Performance Capture with Cloth Simulation

Tao Yu (Beihang University)*:

Zerong Zheng (Tsinghua University):

Yuan Zhong (Tsinghua University):

Jianhui Zhao (Beihang University):

Qionghai Dai (Tsinghua University): http://media.au.tsinghua.edu.cn/people.jsp

Gerard Pons-Moll (MPII, Germany): https://ps.is.tuebingen.mpg.de/person/gpons

Yebin Liu (Tsinghua University): http://media.au.tsinghua.edu.cn/liuyebin.jsp

【Human parsing】Si Clo Pe: Silhouette-based Clothed People

Ryota Natsume (Waseda University):

Shunsuke Saito (University of Southern California)*:

Zeng Huang (University of Southern California):

Weikai Chen (USC Institute for Creative Technology):

Chongyang Ma (Kwai Inc.):

Shigeo Morishima (Waseda Research Institute for Science and Engineering):

Hao Li (Pinscreen/University of Southern California/USC ICT): https://www.hao-li.com/Hao_Li/Hao_Li_-_about_me.html

【Human parsing】Detailed Human Shape Estimation from a Single Image by Hierarchical Mesh Deformation

Hao Zhu (Nanjing University)*:

Xinxin Zuo (University of Kentucky):

Sen Wang (Northwestern Polytechnical University):

Xun Cao (Nanjing University):

Ruigang Yang (University of Kentucky, USA): http://vis.uky.edu/~ryang/

【Human parsing】Learning the Depths of Moving People by Watching Frozen People

Zhengqi Li (Cornell University)*:

Tali Dekel (Google):

Forrester Cole (Google Research):

Richard Tucker (Google):

Ce Liu (Google): http://people.csail.mit.edu/celiu/

Bill Freeman (Google): https://billf.mit.edu/

Noah Snavely (Cornell University and Google AI): http://www.cs.cornell.edu/~snavely/

【Human parsing】Learning 3D Human Dynamics from Video

Angjoo Kanazawa (University of California Berkeley)*:

Jason Zhang (University of California Berkeley):

Panna Felsen (University of California Berkeley):

Jitendra Malik (University of California at Berkley): http://www.cs.berkeley.edu/~malik/

【Human parsing】Multi-person Articulated Tracking with Spatial and Temporal Embeddings

Sheng Jin (Tsinghua University):

Wentao Liu (Sensetime)*:

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Chen Qian (Sense Time):

【Human parsing】Multi-Person Pose Estimation with Enhanced Channel-wise and Spatial Information

Kai Su (Southeast University)*:

Dongdong Yu (Byte Dance):

Zhenqi Xu (Bytedance):

Xin Geng (Southeast University):

Changhu Wang (Byte Dance.Inc):

【Human parsing】High-Resolution Representation Learning for Human Pose Estimation

Ke Sun (University of Science and Technology of China):

Bin Xiao (MSR Asia):

Dong Liu (University of Science and Technology of China):

Jingdong Wang (Microsoft Research)*:

【Human parsing】Graphonomy: Universal Human Parsing via Graph Transfer Learning

Ke Gong (Sun Yat-sen University ):

Yiming Gao (Sun Yat-sen University):

Xiaodan Liang (Sun Yat-sen University)*:

Xiaohui Shen (Byte Dance AI Lab):

Meng Wang (Hefei University of Technology):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

【Human parsing】Neural Scene Decomposition for Human Motion Capture

Helge Rhodin (EPFL)*:

Victor Constantin (EPFL):

Isinsu Katircioglu (EPFL):

Mathieu Salzmann (EPFL):

Pascal Fua (EPFL, Switzerland): http://cvlabwww.epfl.ch/~fua/

【Human parsing】Synergistic, Part-Based 3D Human Reconstruction In-The-Wild

Alp Guler (Imperial College London)*:

Iasonas Kokkinos (UCL): http://cvn.ecp.fr/personnel/iasonas/index.html

【Human parsing】Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

Georgios Pavlakos (University of Pennsylvania)*:

Michael J. Black (Max Planck Institute for Intelligent Systems): http://ps.is.tue.mpg.de/person/black

Timo Bolkart (Max Planck Institute for Intelligent Systems):

Vasileios Choutas (Max Planck Institute for Intelligent Systems):

Nima Ghorbani (Max Planck Institute Tübingen):

Ahmed A A Osman (Max Planck Institute for Intelligent Systems):

Dimitrios Tzionas (Max Planck Institute for Intelligent Systems):

【Human parsing】Pif Paf: Association Fields for Human Pose Estimation

Sven Kreiss (EPFL)*:

Lorenzo Bertoni (EPFL):

Alexandre Alahi (EPFL):

【Human parsing】A Neural Temporal Model for Human Motion Prediction

Anand Gopalakrishnan (Pennsylvania State University)*:

Ankur Mali (Penn State):

Dan Kifer (“Pennsylva State Univ., USA”):

Lee Giles (Pennsylvania State):

Alexander Ororbia (Rochester Institute of Techonology):

【Crowd analysis】Recurrent Attentive Zooming for Joint Crowd Counting and Precise Localization

Chenchen Liu (Peking University):

Xinyu Weng (Peking University):

Yadong Mu (Peking University)*:

【Crowd analysis】Density Map Regression Guided Detection Network for RGB-D Crowd Counting and Localization

Dongze Lian (Shanghaitech University)*:

Jing Li (Shanghai Tech University):

Jia Zheng (Shanghai Tech University):

Weixin Luo (Shanghaitech University):

Shenghua Gao (Shanghaitech University):

【Crowd analysis】ADCrowd Net: An Attention-injective Deformable Convolutional Network for Crowd Understanding

Ning Liu (Sun Yat-sen University )*:

Yongchao Long (Sun Yat-sen University ):

Changqing Zou (University of Maryland (UMD)):

Qun Niu (Sun Yat-sen University):

Li Pan (Shanghai Jiaotong University, China):

Hefeng Wu (Guangdong University of Foreign Studies):

【Crowd analysis】Residual Regression with Semantic Prior for Crowd Counting

Jia Wan (City University of Hong Kong)*:

Wenhan Luo (Tencent AI Lab):

Baoyuan Wu (Tencent AI Lab):

Antoni Chan (City University of Hong Kong, Hong, Kong): http://www.cs.cityu.edu.hk/~abchan/

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Crowd analysis】Context-Aware Crowd Counting

Weizhe Liu (EPFL)*:

Mathieu Salzmann (EPFL):

Pascal Fua (EPFL, Switzerland): http://cvlabwww.epfl.ch/~fua/

【Crowd analysis】Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network

Xiaolong Jiang (Beihang Unviersity)*:

Zehao Xiao (Beihang University):

Baochang Zhang (Beihang University):

Xiantong Zhen (Inception Institute of Artificial Intelligence):

Xianbin Cao (Beihang University, China):

David Doermann (University at Buffalo):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Crowd analysis】Point in, Box out: Beyond Counting Persons in Crowds

yuting liu (sichuan university)*:

Miaojing Shi (Inria Rennes):

Qijun Zhao (Sichuan University):

Xiaofang Wang (Inria Rennes):

【Crowd analysis】Revisiting Perspective Information for Efficient Crowd Counting

Miaojing Shi (Inria Rennes)*:

Zhaohui Yang (Peking University):

Chao Xu (Peking University):

Qijun Chen (Tongji University):

【Crowd analysis】Learning from Synthetic Data for Crowd Counting in the Wild

Qi Wang (Northwestern Polytechnical University)*:

Junyu Gao (Northwestern Polytechnical University, Center for OPTical IMagery Analysis and Learning):

Wei Lin (Northwestern Polytechnical University, Center for OPTical IMagery Analysis and Learning):

Yuan Yuan (Northwestern Polytechnical University):

【Crowd analysis】Wide-Area Crowd Counting via Ground-Plane Density Maps and Multi-View Fusion CNNs

Qi ZHANG (City University of Hong Kong, Hong Kong):

Antoni Chan (City University of Hong Kong, Hong, Kong)*: http://www.cs.cityu.edu.hk/~abchan/

【Crowd analysis】Deep Robust Subjective Visual Property Prediction in Crowdsourcing

Qianqian Xu (Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences):

Zhiyong Yang (SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences:

SCS, University of Chinese Academy of Sciences):

Yangbangyan Jiang (SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences:

SCS, University of Chinese Academy of Sciences):

Xiaochun Cao (Chinese Academy of Sciences):

Qingming Huang (University of Chinese Academy of Sciences)*:

Yuan Yao (Hong Kong University of Science and Technology):

【Crowd analysis】An End-to-End Network for Generating Social Relationship Graphs

Arushi Goel (Agency for Science, Technology and Research)*:

Keng Teck Ma (Agency for Science, Technology and Research):

Cheston Tan (Institute for Infocomm Research, Singapore):

【Crowd analysis】Leveraging Heterogeneous Auxiliary Tasks to Assist Crowd Counting

Muming Zhao (University of Technology, Sydney)*:

Jian Zhang (UTS):

Chongyang Zhang (Shanghai Jiao Tong University):

Wenjun Zhang (Shanghai Jiao Tong University):

【Face recognition】Linkage Based Face Clustering via Graph Convolution Network

Zhongdao Wang (Tsinghua University)*:

Liang Zheng (Australian National University):

Ya-Li Li (THU):

Shengjin Wang (Tsinghua University):

【Face recognition】Deep Face Recognition via Exclusive Regularization

Kai Zhao (Nankai University)*:

Jingyi Xu (Nankai University):

Ming-Ming Cheng (Nankai University):

【Face recognition】Learning to Cluster Faces on an Affinity Graph

Lei Yang (The Chinese University of Hong Kong)*:

Xiaohang Zhan (The Chinese University of Hong Kong):

Dapeng Chen (Sensetime Group Limited):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

【Face recognition】Uniform Face: Learning Deep Equidistributed Representation for Face Recognition

Yueqi Duan (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【Face recognition】Group Sampling Networks for Scale Invariant Face Detection

Xiang Ming (Xi’an Jiaotong University)*:

Fangyun Wei (Microsoft Research Asia):

Ting Zhang (MSRA):

Dong Chen (Microsoft Research Asia):

Fang Wen (Microsoft Research Asia ):

【Face recognition】LAEO-Net: revisiting people Looking At Each Other in videos

Manuel J. Marín-Jiménez (University of Córdoba)*:

Vicky Kalogeiton (University of Oxford):

Pablo Medina Suárez (University of Cordoba):

Andrew Zisserman (University of Oxford): http://www.robots.ox.ac.uk/~vgg/

【Face recognition】Face Anti-Spoofing: Model Matters, So Does Data

Xiao Yang (Tencent AI Lab:

SJTU):

Wenhan Luo (Tencent AI Lab):

Linchao Bao (Tencent AI Lab):

Yuan Gao (Tencent AI Lab):

dihong gong (Tencent AI Lab):

Shibao Zheng (SJTU):

Zhifeng Li (Tencent AI Lab)*:

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Face recognition】Decorrelated Adversarial Learning for Age-Invariant Face Recognition

Hao Wang (Tencent AI Lab)*:

dihong gong (Tencent AI Lab):

Zhifeng Li (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Face recognition】DSFD:Dual Shot Face Detector

Jian Li (Nanjing University of Science and Technology)*:

Yabiao Wang (Tencent):

Changan Wang (Huazhong University of Science and Technology):

Ying Tai (Tencent You Tu):

Jianjun Qian (Nanjing University of Science and Technology):

Jian Yang (Nanjing University of Science and Technology):

Chengjie Wang (Tencent):

Jilin Li (Tencent):

Feiyue Huang (Tencent):

【Face recognition】Feature Transfer Learning for Face Recognition with Under-Represented Data

Xi Yin (Microsoft Could & AI)*:

Xiang Yu (NEC Labs):

Kihyuk Sohn (NEC Labs America):

Xiaoming Liu (Michigan State University):

Manmohan Chandraker (NEC Labs America): http://cseweb.ucsd.edu/~mkchandraker/

【Face recognition】Arc Face: Additive Angular Margin Loss for Deep Face Recognition

Jiankang Deng (Imperial College London)*:

Jia Guo (Deep Insight):

Niannan Xue (Imperial College London):

Stefanos Zafeiriou (Imperial College Londong):

【Face recognition】Led3D: A Lightweight and Efficient Deep Approach to Recognizing Low-quality 3D Faces

Guodong Mu (Beihang University):

Di Huang (Beihang University, China)*:

Guosheng Hu (Any Vision):

Jia Sun (Beihang University):

Yunhong Wang (State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China): http://irip.buaa.edu.cn/Chinese.html

【Face recognition】Efficient Decision-based Black-box Adversarial Attacks on Face Recognition

Yinpeng Dong (Tsinghua University)*:

Hang Su (Tsinghua Univiersity):

Baoyuan Wu (Tencent AI Lab):

Zhifeng Li (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Tong Zhang (Tecent AI Lab): http://tongzhang-ml.org/

Jun Zhu (Tsinghua University):

【Face recognition】FA-RPN: Floating Region Proposals for Face Detection

Mahyar Najibi (University of Maryland)*:

Bharat Singh (Amazon):

Larry Davis (University of Maryland): http://www.umiacs.umd.edu/~lsd/

【Face recognition】Unequal-training for deep face recognition with long-tailed noisy data

Yaoyao Zhong (Beijing University of Posts and Telecommunications)*:

Mei Wang (Beijing University of Posts and Telecommunications):

Jiani Hu (Beijing University of Posts and Telecommunications):

Weihong Deng (Beijing University of Posts and Telecommunications):

Jianteng Peng (Canon Information Technology (Beijing) Co., Ltd):

Xunqiang Tao (Canon Information Technology (Beijing) Co., Ltd):

Yaohai Huang (Canon Information Technology (Beijing) Co., Ltd):

【Face recognition】R3 Adversarial Network for Cross Model Face Recognition

ken chen (sensetime):

Yichao Wu (Sensetime Group Limited)*:

Haoyu Qin (Sensetime):

Ding Liang (Sensetime Group Limited):

Xuebo Liu (Sense Time Group Ltd):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

【Face recognition】Noise-Tolerant Paradigm for Training Face Recognition CNNs

Wei Hu ( Beijing University of Chemical Technology):

Yangyu Huang (Yunshitu Corp.)*:

Fan Zhang (Beijing University of Chemical Technology):

Ruirui Li (Beijing University of Chemical Technology):

【Face recognition】Low-Rank Laplacian-Uniform Mixed Model for Robust Face Recognition

Jiayu Dong (Sun Yat-sen University):

Huicheng Zheng (Sun Yat-sen University)*:

Lina Lian (Sun Yat-sen University):

【Face recognition】Adaptive Face: Adaptive Margin and Sampling for Face Recognition

Hao Liu (NLPR, CASIA):

Xiangyu Zhu (NLPR):

Zhen Lei (NLPR, CASIA, China)*:

Stan Li (National Lab. of Pattern Recognition, China): http://www.cbsr.ia.ac.cn/users/szli/

【Face parsing】A Dataset and Benchmark for Large-scale Multi-modal Face Anti-Spoofing

Shifeng Zhang (CBSR, NLPR, CASIA)*:

Xiaobo Wang (JD AI Research):

Ajian Liu (MUST):

Chenxu Zhao (JD AI Research):

Jun Wan (NLPR, CASIA):

Sergio Escalera (Computer Vision Center (UAB) & University of Barcelona,): http://sergioescalera.com/

Hailin Shi (JD AI Research):

Zezheng Wang (Jingdong Finance):

Stan Li (National Lab. of Pattern Recognition, China): http://www.cbsr.ia.ac.cn/users/szli/

【Face parsing】Morphable Model-based Multi-view 3D Face Reconstruction with Convolutional Neural Networks

Fanzi Wu ( The Chinese University of Hong Kong):

Linchao Bao (Tencent AI Lab)*:

Yonggen Ling (Tencent AI Lab):

Yibing Song (Tencent AI Lab):

Yajing Chen (Shanghai Jiao Tong University):

Songnan Li (The Chinese University of Hong Kong):

King N. Ngan (CUHK, UESTC):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Face parsing】Towards High-fidelity Nonlinear 3D Face Morphoable Model

Luan Tran (Michigan State University)*:

Feng Liu (Michigan State University): http://web.cecs.pdx.edu/~fliu/

Xiaoming Liu (Michigan State University):

【Face parsing】Bridge Net: A Continuity-Aware Probabilistic Network for Age Estimation

Wanhua Li (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Jianjiang Feng (Tsinghua University):

Chunjing Xu (Huawei Noah’s Ark Lab):

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Face parsing】GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction

Baris Gecer (Imperial College London)*:

Stylianos Ploumpis (Imperial College London):

Irene Kotsia (Hellenic Open University):

Stefanos Zafeiriou (Imperial College Londong):

【Face parsing】Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation

Yong Zhang (Tencent AI Lab):

Baoyuan Wu (Tencent AI Lab)*:

Weiming Dong (NLPR, Institute of Automation, Chinese Academy of Sciences):

Zhifeng Li (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Bao-Gang Hu (Institute of Automation, Chinese Academy of Sciences):

Qiang Ji (Rensselaer Polytechnic Institute): http://www.ecse.rpi.edu/~qji/

【Face parsing】Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection

Zhiwei Liu ( Institute of Automation Chinese Academy of Sciences):

Xiangyu Zhu (NLPR)*:

Guosheng Hu (Any Vision):

Haiyun Guo (CASIA):

Ming Tang (Chinese Academy of Sciences, China):

Zhen Lei (NLPR, CASIA, China):

Neil Robertson (Queen’s University Belfast):

Jinqiao Wang (Institute of Automation, Chinese Academy of Sciences):

【Face parsing】Robust Facial Landmark Detection via Occlusion-adaptive Deep Networks

Meilu Zhu (College of Computer Science and Software Engineering, Shenzhen University):

Mingjie Zheng (College of Computer Science and Software Engineering, Shenzhen University):

Daming Shi (College of Computer Science and Software Engineering, Shenzhen University)*:

Muhammad Sadiq (College of Computer Science and Software Engineering, Shenzhen University):

【Face parsing】Face Parsing with Ro I Tanh-warping

Jinpeng Lin (Xia Men University):

Hao Yang (Microsoft Research Asia)*:

Dong Chen (Microsoft Research Asia):

Ming Zeng (Software School of Xiamen University):

Fang Wen (Microsoft Research Asia ):

Lu Yuan (Microsoft): http://research.microsoft.com/en-us/um/people/luyuan/index.htm

【Face parsing】A Compact Embedding for Facial Expression Similarity

Raviteja Vemulapalli (Google)*:

Aseem Agarwala (Google):

【Face parsing】MMFace: A Multi-Metric Regression Network for Unconstrained Face Reconstruction

Hongwei Yi (Peking University)*:

Chen Li (Tencent):

Qiong Cao (Tencent):

Xiaoyong Shen (Tencent):

Sheng Li (Peking University):

Guoping Wang (Peking University):

Yu-Wing Tai (Tencent):

【Face parsing】Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision

Soubhik Sanyal (Max Planck Institute for Intelligent Systems)*:

Timo Bolkart (Max Planck Institute for Intelligent Systems):

Haiwen Feng (Max Planck Institute for Intelligent Systems):

Michael J. Black (Max Planck Institute for Intelligent Systems): http://ps.is.tue.mpg.de/person/black

【Face parsing】Joint Face Detection and Facial Motion Retargeting for Multiple Faces

BINDITA CHAUDHURI (University of Washington)*:

Noranart Vesdapunt (Microsoft Research):

Baoyuan Wang (Microsoft Research):

【Face parsing】3D Guided Fine-Grained Face Manipulation

Zhenglin Geng (Stanford University):

Chen Cao (Snap Inc.)*:

Sergey Tulyakov (Snap Inc):

【Face parsing】Neuro-inspired Eye Tracking with Eye Movement Dynamics

Kang Wang (RPI)*:

Hui Su (IBM):

Qiang Ji (Rensselaer Polytechnic Institute): http://www.ecse.rpi.edu/~qji/

【Face parsing】Facial Emotion Distribution Learning by Exploiting Low-Rank Label Correlations Locally

Xiuyi Jia (Nanjing University of Science and Technology)*:

Xiang Zheng (Nanjing University of Science and Technology):

Weiwei Li (Nanjing University of Aeronautics and Astronautics):

Changqing Zhang (Tianjin university):

Zechao Li (Nanjing University of Science and Technology):

【Face parsing】Unsupervised Face Normalization with Extreme Pose and Expression in the Wild

Yichen Qian (Beijing University of Posts and Telecommunications):

Weihong Deng (Beijing University of Posts and Telecommunications)*:

Jiani Hu (Beijing University of Posts and Telecommunications):

【Face parsing】Semantic Component Decomposition for Face Attribute Manipulation

Yingcong Chen (Chinese University of Hong Kong)*:

Xiaohui Shen (Byte Dance AI Lab):

Zhe Lin (Adobe Research): http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Xin Lu (Adobe):

I-Ming Pao (Adobe):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Face parsing】P2SGrad: Refined Gradients for Optimizing Deep Face Models

Xiao Zhang (Chinese University of Hong Kong):

Rui Zhao (Sense Time Group Limited):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

Mengya Gao (Tianjin University):

Yu Qiao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)*: http://mmlab.siat.ac.cn/yuqiao/

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Hongsheng Li (Chinese University of Hong Kong):

【Face parsing】High-Quality Face Capture Using Anatomical Muscles

Michael H Bao (Stanford University)*:

Matthew D Cong (Industrial Light & Magic):

Stephane Grabli (Industrial Light & Magic):

Ronald Fedkiw (Stanford):

【Face parsing】FML: Face Model Learning from Videos

Ayush Tewari (Max Planck Institute for Informatics)*:

Florian Bernard (Max Planck Institute for Informatics):

Pablo Garrido (Technicolor):

Gaurav Bharaj (Technicolor):

Mohamed Elgharib (Max Planck Institute for Informatics):

Hans-Peter Seidel (Max Planck Institute for Informatics):

Patrick Pérez (Valeo.ai):

Michael Zollhoefer (Stanford University):

Christian Theobalt (MPI Informatik):

【Face parsing】Ada Scale: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations

Xiao Zhang (Chinese University of Hong Kong):

Rui Zhao (Sense Time Group Limited):

Yu Qiao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)*: http://mmlab.siat.ac.cn/yuqiao/

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Hongsheng Li (Chinese University of Hong Kong):

【Face parsing】Twin-Cycle Autoencoder: Self-supervised Representation Learning from Entangled Movement for Facial Action Unit Detection

Yong Li (Institute of Computing Technology, Chinese Academy of Sciences):

Jiabei Zeng (Institute of Computing Technology, Chinese Academy on Sciences)*:

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

Xilin Chen (China):

【Face parsing】Combining 3D Morphable Models: A Largescale Face-and-Head Model

Stylianos Ploumpis (Imperial College London)*:

Haoyang Wang (Imperial College London):

Nick E. Pears (University of York, UK):

William Smith (University of York):

Stefanos Zafeiriou (Imperial College Londong):

【Face parsing】Local Relationship Learning with Person-specific Regularization for Facial Action Unit Detection

Xuesong Niu (Institute of Computing Technology, CAS):

Hu Han (Chinese Academy of Sciences)*:

Songfan Yang (100tal):

Yan Huang (TAL Education Group):

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

【Face parsing】Disentangled Representation Learning for 3D Face Shape

Zi-Hang Jiang (University of Science and Technology of China):

Qianyi Wu (University of Science and Technology of China):

Keyu Chen (University of Science and Technology of China):

Juyong Zhang (University of Science and Technology of China)*:

【Face parsing】C3AE: Exploring the Limits of Compact Model for Age Estimation

Chao Zhang (UESTC:

Megvii)*:

Shuaicheng Liu (UESTC:

Megvii):

Xun Xu (NUS):

Ce Zhu (University of Electronic Science & Technology of China):

【Object recognition】Generalized Zero-Shot Recognition based on Visually Semantic Embedding

Pengkai Zhu (Boston University)*:

Hanxiao Wang (Boston University):

Venkatesh Saligrama (Boston University):

【Object recognition】Large-scale Long-Tailed Recognition in an Open World

Ziwei Liu (The Chinese University of Hong Kong)*:

Zhongqi Miao (UC Berkeley):

Xiaohang Zhan (The Chinese University of Hong Kong):

Jiayun Wang (UC Berkeley / ICSI):

Boqing Gong (Tencent AI Lab):

Stella X Yu (UC Berkeley / ICSI):

【Object recognition】Classification-Reconstruction Learning for Open-Set Recognition

Ryota Yoshihashi (The University of Tokyo)*:

Wen Shao (The University of Tokyo):

Rei Kawakami (The University of Tokyo):

Shaodi You (Data61-CSIRO):

Makoto Iida (The University of Tokyo):

Takeshi Naemura (The University of Tokyo):

【Object recognition】Handwriting Recognition in Low-resource Scripts using Adversarial Learning

Ayan Kumar Bhunia (Nanyang Technological University):

Abhirup Das (Institute of Engineering and Management):

Ankan Kumar Bhunia (Jadavpur University):

Sai Raj Kishore Perla (Institute of Engineering & Management):

Partha Pratim Roy (IIT Roorkee)*:

【Object recognition】Looking for the devil in the details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition

Heliang Zheng (USTC)*:

Jianlong Fu (Microsoft Research):

Zheng-Jun Zha (University of Science and Technology of China):

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

【Object recognition】Learning without Memorizing

Prithviraj Dhar (University of Maryland, College Park)*:

Rajat Vikram Singh (Siemens Corporation):

Kuan-Chuan Peng (Siemens Corporation):

Ziyan Wu (Siemens Corporation):

Rama Chellappa (University of Maryland):

【Object recognition】Destruction and Construction Learning for Fine-grained Image Recognition

Yue Chen (JD AI Research)*:

Yalong Bai (JD AI Research):

Wei Zhang (JD AI Research):

Tao Mei (AI Research of JD.com):

【Object recognition】Multi-Label Image Recognition with Graph Convolutional Networks

Zhao-Min Chen (Nan Jing University):

Xiu-Shen Wei (Nanjing University)*:

Peng Wang (The University of Adelaide):

Yanwen Guo (-):

【Object recognition】RAVEN: A Dataset for Relational and Analogical Visual r Easo Ning

Chi Zhang (University of California, Los Angeles)*:

Feng Gao (UCLA):

Baoxiong Jia (UCLA):

Yixin Zhu (UCLA):

Song-Chun Zhu (UCLA): http://www.stat.ucla.edu/~sczhu/

【Object recognition】Compressing Unknown Classes with Product Quantizer for Efficient Zero-Shot Classification

Jin Li (Xi’an Jiaotong University):

Xuguang Lan (Xi’an Jiaotong University)*:

Yang Liu (Xidian University):

Le Wang (Xi’an Jiaotong University):

Nanning Zheng (Xi’an Jiaotong University):

【Object recognition】Orthogonal Decomposition Network for Pixel-wise Binary Classification

Chang Liu (University of Chinese Academy of Sciences)*:

Fang Wan (University of Chinese Academy of Sciences):

Wei Ke (University of Chinese Academy of Sciences):

Zhuowei Xiao (Institute of Geology and Geophysics, Chinese Academy of Sciences):

Yuan Yao (University of Chinese Academy of Sciences):

Xiaosong Zhang (University of Chinese Academy of Sciences):

Qixiang Ye (University of Chinese Academy of Sciences, China): https://ucassdl.cn/content/work/paper.html

【Object recognition】Multispectral Imaging for Fine-Grained Recognition of Powders on Complex Backgrounds

Tiancheng Zhi (Carnegie Mellon University)*:

Bernardo Pires (-):

Martial Hebert (Carnegie Mellon School of Computer Science): http://www.cs.cmu.edu/~hebert/

Srinivasa G Narasimhan (Carnegie Mellon University):

【Object recognition】IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition

Xiaoping Wu (Nankai University):

Chi Zhan (Nankai University):

Yukun Lai (Cardiff University):

Ming-Ming Cheng (Nankai University):

Jufeng Yang (Nankai University )*:

【Object recognition】On zero-shot recognition of generic objects

Tristan E.M Hascoet (Kobe University)*:

【Object recognition】Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset

Martin Mundt (FIAS)*:

Sagnik Majumder (Goethe University):

Sreenivas Narasimha Murali (Karomi):

Panagiotis Panetsos (Egnatia Odos A. E.):

Visvanathan Ramesh (Univ. Frankfurt):

【Object recognition】Direct Object Recognition Without Line-of-sight Using Optical Coherence

Xin Lei (Coherent AI LLC):

Liangyu He (Coherent AI LLC):

Ken Xingze Wang (Coherent AI LLC)*:

Xinggang Wang (Huazhong Univ. of Science and Technology): http://www.xinggangw.info/

Yixuan Tan (University of Wisconsin-Madison):

Yihan Du (Huazhong Univ. of Science and Technology):

Shanhui Fan (Stanford University):

Zongfu Yu (University of Wisconsin Madison):

【Object detection】Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

Hamid Rezatofighi (University of Adelaide)*:

Nathan Tsoi (Stanford University):

Jun Young Gwak (Stanford University):

Amir A Sadeghian (Stanford):

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

【Object detection】Adapting Object Detectors via Selective Cross-Domain Alignment

Xinge Zhu (The Chinese University of Hong Kong)*:

Jiangmiao Pang (Zhejiang University):

Ceyuan Yang (Chinese University of Hong Kong):

Jianping Shi (Sensetime Group Limited):

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

【Object detection】Automatic adaptation of object detectors to new domains using self-training

Aruni Roy Chowdhury (University of Massachusetts, Amherst)*:

Prithvijit Chakrabarty (University of Massachusetts, Amherst):

Ashish Singh (UMASS Amherst):

Sou Young Jin (UMASS Amherst):

Huaizu Jiang (UMass Amherst):

Liangliang Cao (UMass Amherst): http://researcher.watson.ibm.com/researcher/view.php?person=us-liangliang.cao

Erik Learned-Miller (University of Massachusetts, Amherst):

【Object detection】Libra R-CNN: Balanced Learning for Object Detection

Jiangmiao Pang (Zhejiang University)*:

Kai Chen (The Chinese University of Hong Kong):

Jianping Shi (Sensetime Group Limited):

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

Huajun Feng (Zhejiang Univerisity):

【Object detection】Feature Selective Anchor-Free Module for Single-Shot Object Detection

Chenchen Zhu (Carnegie Mellon University)*:

Yihui He (Carnegie Mellon University):

Marios Savvides (Carnegie Mellon University):

【Object detection】Bottom-up Object Detection by Grouping Extreme and Center Points

Xingyi Zhou (The University of Texas at Austin)*:

Jiacheng Zhuo (The University of Texas at Austin):

Philipp Kraehenbuehl (UT Austin): https://www.philkr.net/

【Object detection】Unsupervised Moving Object Detection via Contextual Information Separation

Yanchao Yang (UCLA)*:

Antonio Loquercio (ETH / University of Zurich):

Davide Scaramuzza (University of Zurich & ETH Zurich, Switzerland): http://rpg.ifi.uzh.ch/people_scaramuzza.html

Stefano Soatto (UCLA): http://vision.ucla.edu/projects.html

【Object detection】SIXray: A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images

Caijing Miao (University of Chinese Academy of Sciences)*:

Lingxi Xie (Johns Hopkins University):

Fang Wan (University of Chinese Academy of Sciences):

Chi Su (Kingsoft Cloud):

Hongye Liu (Kingsoft Cloud):

Jianbin Jiao (University of Chinese Academy of Sciences):

Qixiang Ye (University of Chinese Academy of Sciences, China): https://ucassdl.cn/content/work/paper.html

【Object detection】Fully Quantized Network for Object Detection

Rundong Li (Shanghai Tech University)*:

Feng Liang (Tsinghua University:

Sense Time):

Hongwei Qin (Sensetime):

Yan Wang (Sense Time):

Rui Fan (Shanghai Tech University):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

【Object detection】C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection

Fang Wan (University of Chinese Academy of Sciences)*:

Chang Liu (University of Chinese Academy of Sciences):

Wei Ke (University of Chinese Academy of Sciences):

Xiangyang Ji (Tsinghua University):

Jianbin Jiao (University of Chinese Academy of Sciences):

Qixiang Ye (University of Chinese Academy of Sciences, China): https://ucassdl.cn/content/work/paper.html

【Object detection】Attention-based Dropout Layer for Weakly Supervised Object Localization

Junsuk Choe (Yonsei University):

Hyunjung Shim (Yonsei University)*:

【Object detection】Scratch Det: Training Single-Shot Object Detectors from Scratch

Rui Zhu (JD AI Research)*:

Shifeng Zhang (CBSR, NLPR, CASIA):

Xiaobo Wang (JD AI Research):

Longyin Wen (JD Digits):

Hailin Shi (JD AI Research):

Liefeng Bo (JD Finance):

Tao Mei (AI Research of JD.com):

【Object detection】Learning Ro I Transformer for Oriented Object Detection in Aerial Images

Jian Ding (Wuhan University):

Nan Xue (Wuhan University):

Yang Long (Wuhan University ):

Gui-Song Xia (Wuhan University)*:

Qikai Lu (Wuhan University):

【Object detection】Bounding Box Regression with Uncertainty for Accurate Object Detection

Yihui He (Carnegie Mellon University)*:

Chenchen Zhu (Carnegie Mellon University):

Jianren Wang (Carnegie Mellon University):

Marios Savvides (Carnegie Mellon University):

Xiangyu Zhang (Megvii Inc):

【Object detection】Activity Driven Weakly Supervised Object Detection

Zhenheng Yang (Facebook Research)*:

Vignesh Ramanathan (Facebook):

Deepti Ghadiyaram (Facebook):

Ram Nevatia (U of Southern California): http://iris.usc.edu/USC-Computer-Vision.html

Dhruv Mahajan (Facebook):

【Object detection】Region Proposal by Guided Anchoring

Kai Chen (The Chinese University of Hong Kong)*:

Jiaqi Wang (CUHK):

Shuo Yang (Amazon):

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

【Object detection】Assessment of Faster-RCNN in Man-Machine collaborative search

Arturo Deza (Harvard University)*:

Amit Surana (United Technologies Resesarch Center):

Miguel Eckstein (UCSB):

【Object detection】Feature Distance Adversarial Network for Vehicle Re-Identification

Yihang Lou (Peking University)*:

YAN BAI (Peking University):

Jun Liu (Nanyang Technological University):

Shiqi Wang (City U):

Lingyu Duan (Peking University):

【Object detection】Part-regularized Near-Duplicate Vehicle Re-identification

Bing He (Beihang University):

Jia Li (Beihang University)*:

Yifan Zhao (Beihang University):

Yonghong Tian (PKU):

【Object detection】Learning Shape-Aware Embedding for Scene Text Detection

Zhuotao Tian (Chinese University of Hong Kong)*:

Michelle Shu (the Johns Hopkins University):

Pengyuan Lyu (Tencent):

Ruiyu Li (Tencent):

Chao Zhou (Tencent):

Xiaoyong Shen (Tencent):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Object detection】Distilling Object Detectors with Fine-grained Feature Imitation

tao wang (national university of singapore)*:

Jiashi Feng (NUS): https://sites.google.com/site/jshfeng/

Li Yuan (National University of Singapore):

Xiaopeng Zhang (Noah’s Ark Lab, Huawei Inc.):

【Object detection】Multi-task Self-Supervised Object Detection via Recycling of Bounding Box Annotations

Wonhee Lee (Seoul National University)*:

Joonil Na (Seoul National University):

Gunhee Kim (Seoul National University): http://www.cs.cmu.edu/~gunhee/index.html

【Object detection】Towards Accurate One-Stage Object Detection with AP-Loss

Kean Chen (Shanghai Jiao Tong University)*:

Weiyao Lin (Shanghai Jiao Tong university):

Jianguo Li (Intel Labs):

John See (Multimedia University):

Ji Wang (Tencent):

Lingyu Duan (Peking University):

Zhibo Chen (Tencent):

Changwei He (Tencent):

Junni Zou (Shanghai Jiao Tong University):

【Object detection】On Exploring Indeterminate Relationships for Visual Relationship Detection

Yibing Zhan (Hangzhou Dianzi University):

Jun Yu (HDU)*:

Ting Yu (Hangzhou Dianzi University):

Dacheng Tao (University of Sydney):

【Object detection】Distraction-aware Shadow Detection

Quanlong Zheng (City University of Hong Kong):

Xiaotian Qiao (City University of Hong Kong):

Ying Cao (City University of Hong Kong)*:

Rynson W.H. Lau (City University of Hong Kong):

【Object detection】Rep Met: Representative-based metric learning for classification and few-shot object detection

Leonid Karlinsky (IBM-Research)*:

Joseph Shtok (IBM-Reseach):

Sivan Harary (IBM-Research):

Eli Schwartz (Tel-Aviv University):

Amit Aides (IBM):

Rogerio Feris (IBM Research AI, MIT-IBM Watson AI Lab): http://rogerioferis.com/

Raja Giryes (Tel Aviv University):

Alex Bronstein (Technion):

【Object detection】Precise Detection in Densely Packed Scenes

Eran Goldman (Bar Ilan University):

Roei Herzig (Tel Aviv University):

Aviv Eisenschtat (Trax):

Jacob Goldberger (BIU):

Tal Hassner (Open University of Israel)*:

【Object detection】H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactions

Bugra Tekin (Microsoft)*:

Federica Bogo (Microsoft):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

【Object detection】Re-Identification with Consistent Attentive Siamese Networks

Meng Zheng (Rensselaer Polytechnic Institute):

Srikrishna Karanam (Siemens Corporate Technology, Princeton)*:

Ziyan Wu (Siemens Corporation):

Richard Radke (Rensselaer Polytechnic Institute):

【Object detection】Inverse Discriminative Networks for Handwritten Signature Verification

Huan Li (Xi’an Jiaotong University):

Ping Wei (Xi’an Jiaotong University)*:

Ping Hu (Xi’an Jiaotong University):

【Object detection】Strong-Weak Distribution Alignment for Adaptive Object Detection

Kuniaki Saito (Boston University)*:

Yoshitaka Ushiku (The University of Tokyo):

Tatsuya Harada (The University of Tokyo):

Kate Saenko (Boston University):

【Object detection】NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection

Golnaz Ghiasi (Google Brain)*:

Tsung-Yi Lin (Google Brain):

Quoc Le (Google Brain):

【Object detection】PPGNet: Learning Point-Pair Graph for Line Segment Detection

Ziheng Zhang (Shanghaitech University):

Zhengxin Li (Shanghai Tech University)*:

Ning Bi (Shanghaitech University):

Jia Zheng (Shanghai Tech University):

Jinlei Wang (Shanghaitech University):

Kun Huang (Shanghai Tech):

Weixin Luo (Shanghaitech University):

Yanyu Xu (Shanghaitech University):

Shenghua Gao (Shanghaitech University):

【Object detection】Reasoning-RCNN: Unifying Adaptive Global Reasoning into Large-scale Object Detection

Hang Xu (Huawei Noah’s Ark Lab):

Chen Han Jiang (Sun Yat-sen University):

Xiaodan Liang (Sun Yat-sen University)*:

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

Zhenguo Li (Huawei Noah’s Ark Lab):

【Object detection】Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation

Xiaobing Wang (Samsung Research Institute China-Beijing)*:

yingying jiang ( Samsung Research China,Beijing):

Zhenbo Luo ( Samsung Research Institute China-Beijing):

Cheng-lin Liu (Institute of Automation of Chinese Academy of Sciences):

Hyunsoo Choi (SAMSUNG ELECTRONICS CO.,LTD):

Sungjin Kim (SAMSUNG ELECTRONICS CO.,LTD):

【Object detection】Locating Objects Without Bounding Boxes

Javier Ribera (Purdue University)*:

David Güera (Purdue University):

Yuhao Chen (Purdue University):

Edward Delp (Purdue University):

【Object detection】Sampling Techniques for Large-Scale Object Detection from Sparsely Annotated Objects

Yusuke Niitani (Preferred Networks, Inc.)*:

Takuya Akiba (Preferred Networks, Inc.):

Tommi Kerola (Preferred Networks, Inc.):

Toru Ogawa (Preferred Networks, Inc.):

Shotaro Sano (Preferred Networks, Inc.):

Shuji Suzuki (Preferred Networks, Inc.):

【Object detection】Few Shot Adaptive Faster R-CNN

tao wang (national university of singapore)*:

Jiashi Feng (NUS): https://sites.google.com/site/jshfeng/

Li Yuan (National University of Singapore):

Xiaopeng Zhang (Noah’s Ark Lab, Huawei Inc.):

【Object detection】Moving Object Detection under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition

Moein Shakeri (University of Alberta)*:

Zhang Hong (University of Alberta):

【Object detection】Towards Robust Curve Text Detection with Conditional Spatial Expansion

ZICHUAN LIU (Nanyang Technological University)*:

Guosheng Lin (Nanyang Technological University):

Sheng Yang (Nanyang Technological University):

Fayao Liu (University of Adelaide):

Weisi Lin (“Nanyang Technological University, Singapore”):

Wang Ling Goh (Nanyang Technological University):

【Object detection】Towards Universal Object Detection by Domain Attention

Xudong Wang (University of California, San Diego)*:

Zhaowei Cai (UCSD):

Dashan Gao (12 Sigma Technologies):

Nuno Vasconcelos (UCSD, USA): http://www.svcl.ucsd.edu/

【Object detection】Efficient Featurized Image Pyramid Network for Single Shot Detector

Yanwei Pang (Tianjin University):

Tiancai Wang (Tianjin University)*:

Rao Muhammad Anwer (Inception Institute of Artificial Intelligence ):

Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Object detection】Multi-Task Multi-Sensor Fusion for 3D Object Detection

Ming Liang (Uber ATG):

Bin Yang (Uber ATG & University of Toronto)*:

Yun Chen (Uber ATG Toronto):

Rui Hu (Uber):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Object detection】Grid R-CNN

Xin Lu (Zhejiang University)*:

Buyu LI (The Chinese University of Hong Kong):

Yuxin Yue (Beihang University):

Quanquan Li (Sense Time Group Limited):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

【Object detection】Exploring the Bounds of the Utility of Context for Object Detection

Ehud Barnea (Ben-Gurion University, Beer Sheva, Israel)*:

Ohad Ben-Shahar (Ben Gurion University, Israel):

【Object detection】What Object Should I Use? – Task Driven Object Detection

Johann Sawatzky (University of Bonn)*:

Yaser Souri (University of Bonn):

Christian Grund (University of Bonn):

Jürgen Gall (University of Bonn):

【Object detection】Triangulation Learning Network: from Monocular to Stereo 3D Object Detection

Zengyi Qin (Tsinghua University):

Jinglu Wang (Microsoft Research Asia)*:

Yan Lu (Microsoft Research Asia):

【Object detection】Assisted Excitation of Activations: A Learning Technique to Improve Object Detectors

Mohammad Mahdi Derakhshani (University of Tehran):

saeed masoudnia (university of tehran):

Amirhossein Shaker (university of Tehran):

Omid Mersa (University of Tehran):

Mohammad Amin Sadeghi (University of Tehran):

Mohammad Rastegari (Allen Institute for Artificial Intelligence)*:

Babak Nadjar Araabi (Tehran University):

【Object detection】Spatial-aware Graph Relation Network for Large-scale Object Detection

Hang Xu (Huawei Noah’s Ark Lab):

Chen Han Jiang (Sun Yat-sen University):

Xiaodan Liang (Sun Yat-sen University)*:

Zhenguo Li (Huawei Noah’s Ark Lab):

【Object detection】Shape Robust Text Detection with Progressive Scale Expansion Network

Wenhai Wang (Nanjing university):

Xiang Li (NJUST):

Enze Xie (Tongji University):

Wenbo Hou (Nanjing University):

Tong Lu (Nanjing University)*:

Gang Yu (Face++):

Shuai Shao (Megvii (Face++)):

【Object detection】Maxpool NMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors

Lile Cai (Institute for Infocomm Research)*:

Bin Zhao (Nil):

Zhe Wang (I2R):

Jie Lin (Institute for Infocomm Research (I2R), Singapore):

Chuan Sheng Foo (Institute for Infocomm Research, A*STAR):

Mohamed Sabry Aly (Nanyang Technological University):

Vijay Chandrasekhar (Institute for Infocomm Research):

【Object detection】Character Region Awareness for Text Detection

Youngmin Baek ( Clova AI Research, NAVER Corp.)*:

Bado Lee (Clova AI Research, NAVER Corp.):

Dongyoon Han (Clova AI Research, NAVER Corp.):

Sangdoo Yun ( Clova AI Research, NAVER Corp.):

Hwalsuk Lee ( Clova AI Research, NAVER Corp.):

【Object detection】You reap what you sow: Generating High Precision Object Proposals for Weakly-supervised Object Detection

Krishna Kumar Singh (University of California Davis)*:

Yong Jae Lee (University of California, Davis):

【Object detection】Dissimilarity Coefficient based Weakly Supervised Object Detection

Aditya Arun (IIIT Hyderabad)*:

C.V. Jawahar (IIIT-Hyderabad):

  1. Pawan Kumar (University of Oxford):

【Object detection】Object detection with location-aware deformable convolution and backward attention filtering

Chen Zhang (Illinois Institute of Technology)*:

Joohee Kim (Illinois Institute of Technology):

【Object detection】Incremental Object Learning from Contiguous Views

Stefan Stojanov (Georgia Institute of Technology)*:

Samarth Mishra (Georgia Institute of Technology):

Ngoc Anh Thai (Georgia Institute of Technology):

Nikhil Dhanda (Georgia Institute of Technology):

Ahmad Humayun (Georgia Institute of Technology):

Linda Smith (Indiana University):

Chen Yu (Indiana University):

James Rehg (Georgia Institute of Technology): http://www.cc.gatech.edu/~rehg/

【Object detection】Tightness-aware Evaluation Protocol for Scene Text Detection

Yuliang Liu (South China University of Technology):

Lianwen Jin (South China University of Technology)*:

Zecheng Xie (South China University of Technology):

Canjie Luo (South China University of Technology):

Lele Xie (South China University of Technology):

Shuaitao Zhang (South China University of Technology):

【Object detection】Object Discovery in Videos as Foreground Motion Clustering

Christopher Xie (University of Washington)*:

Yu Xiang (Nvidia):

Dieter Fox (NVIDIA):

Zaid Harchaoui (University of Washington):

【Object detection】Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes

Chengquan Zhang (Baidu Inc)*:

Borong Liang (Xiamen University):

Zuming Huang (Baidu Inc.):

Mengyi En (Baidu Inc.):

Junyu Han (Baidu Inc.):

Errui Ding (Baidu Inc.):

Xinghao Ding (Xiamen University):

【Object detection】Attention Based Glaucoma Detection: A Large-scale Database and CNN Model

Liu Li (BUAA):

Xiaofei Wang (Bei Hang University):

Lai Jiang (BUAA):

Hanruo Liu (Beijing Tongren Hospital, Capital Medical University):

Mai Xu (BUAA)*:

【Object detection】Privacy Protection in Street-View Panoramas using Depth and Multi-View Imagery

Ries M.C. Uittenbogaard (Royal IHC):

Clint Sebastian (Eindhoven University of Technology)*:

Julien A. Vijverberg (Cyclo Media B.V.):

Bas Boom (Cyclomedia):

Dariu Gavrila (TU Delft):

  1. H. N. de With (Eindhoven University of Technology):

【Object detection】Where’s Wally now? Deep Generative and Discriminative Embeddings for Novelty Detection

Philippe Burlina (JHU/APL/CS/SOM)*:

Neil Joshi (Johns Hopkins U.):

i_jeng Wang (Johns Hopkins U.):

【Object detection】Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction

Jason Ku (University of Toronto)*:

Alex D Pon (University of Toronto):

Steven L Waslander (University of Toronto):

【Object detection】Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection

Taekyung Kim (KAIST):

Minki Jeong (KAIST):

Seunghyeon Kim (KAIST):

Seokeon Choi (KAIST):

Changick Kim (KAIST)*:

【Object detection】Cascaded Generative and Discriminative Learning for Microcalcification Detection in Breast Mammograms

Fandong Zhang (Peking University)*:

Ling Luo (Beijing University of Posts and Telecommunications):

Xinwei Sun (Peking University):

Zhen Zhou (Peking University):

Xiuli Li (Deepwise Inc.):

Yizhou Wang (PKU):

Yizhou Yu (Deepwise AI Lab): http://i.cs.hku.hk/~yzyu/

【Object detection】An Alternative Deep Feature Approach to Line Level Keyword Spotting

George Retsinas (NCSR Demokritos)*:

Georgios Louloudis (NCSR Demokritos):

Nikolaos Stamatopoulos (NCSR Demokritos):

Giorgos Sfikas (NCSR Demokritos):

Basilis Gatos (NCSR Demokritos):

【Saliency detection】PAGE-Net: Salient Object Detection with Pyramid Attention and Salient Edge

Wenguan Wang (Inception Institute of Artificial Intelligence):

Shuyang Zhao (Beijing Institute of Technology ):

Jianbing Shen (Beijing Institute of Technology)*: http://cs.bit.edu.cn/shenjianbing/

Steven Hoi (SMU):

Ali Borji (University of Central Florida): http://ilab.usc.edu/borji/

【Saliency detection】Attentive Feedback Network for Boundary-Aware Salient Object Detection

Mengyang Feng (Dalian University of Technology):

Huchuan Lu (Dalian University of Technology)*: http://ice.dlut.edu.cn/lu/index.html

Errui Ding (Baidu Inc.):

【Saliency detection】Pyramid Feature Selective Network for Saliency detection

Ting Zhao (Harbin Institute of Technology, China)*:

XIANGQIAN WU (Harbin Institute of Technology, China):

【Saliency detection】Co-saliency Detection via Mask-guided Fully Convolutional Networks with Multi-scale Label Smoothing

Kaihua Zhang (NUIST)*:

Tengpeng Li (NUIST):

Bo Liu (Rutgers University):

Qingshan Liu (Nanjing University of Information Science & Technology):

【Saliency detection】Cascaded Partial Decoder for Fast and Accurate Salient Object Detection

Zhe Wu (University of Chinese Academy of Sciences)*:

Li Su (University of Chinese Academy of Sciences):

Qingming Huang (University of Chinese Academy of Sciences):

【Saliency detection】A Simple Pooling-Based Design for Real-Time Salient Object Detection

Jiang-Jiang Liu (Nankai University)*:

Qibin Hou (Nankai University):

Ming-Ming Cheng (Nankai University):

Jiashi Feng (NUS): https://sites.google.com/site/jshfeng/

Jianmin Jiang (Shenzhen University):

【Saliency detection】Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection

Jiaxing Zhao (Nankai University):

Yang Cao (Nankai University):

Deng-Ping Fan (Nankai University):

Xuan-Yi Li (Nankai University):

Le Zhang (Institute for Infocomm Research,Agency for Science, Technology and Research (A*STAR)):

Ming-Ming Cheng (Nankai University)*:

【Saliency detection】Emotion-Aware Human Attention Prediction

Macario II O Cordel (De La Salle University)*:

Shaojing Fan (National University of Singapore):

Zhiqi Shen (National University of Singapore):

Mohan Kankanhalli (National University of Singapore,):

【Saliency detection】Did it change? Learning to Detect Point-of-Interest Changes for Proactive Map Updates

Jerome Revaud (Naver Labs Europe)*: http://lear.inrialpes.fr/people/revaud/

Minhyeok Heo (Naver LABS):

Rafael S Rezende (Naver Labs):

Chanmi You (Naver Labs):

Seong-Gyun Jeong (Naver Labs):

【Saliency detection】Pay attention! – Robustifying a Deep Visuomotor Policy through Task-Focused Visual Attention

Pooya Abolghasemi (University of Central Florida)*:

Amir Mazaheri (University of Central Florida):

Ladislau Boloni (University of Central Florida):

Mubarak Shah (University of Central Florida): http://crcv.ucf.edu/people/faculty/shah.html

【Saliency detection】An Iterative and Cooperative Top-down and Bottom-up Inference Network for Salient Object Detection

Wenguan Wang (Inception Institute of Artificial Intelligence):

Jianbing Shen (Beijing Institute of Technology)*: http://cs.bit.edu.cn/shenjianbing/

Ming-Ming Cheng (Nankai University):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Saliency detection】Cap Sal: Leveraging Captioning to Boost Semantics for Salient Object Detection

Lu Zhang (Dalian University of Technology):

Huchuan Lu (Dalian University of Technology)*: http://ice.dlut.edu.cn/lu/index.html

Zhe Lin (Adobe Research): http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Jianming Zhang (Adobe Research):

You He (Naval Aviation University):

【Saliency detection】Multi-source weak supervision for saliency detection

Yu Zeng (Dalian University of Technology)*:

Huchuan Lu (Dalian University of Technology): http://ice.dlut.edu.cn/lu/index.html

Lihe Zhang (Dalian University of Technology):

Yunzhi Zhuge (Dalian University of Technology):

Mingyang Qian (Dalian University of Technology):

Yizhou Yu (Deepwise AI Lab): http://i.cs.hku.hk/~yzyu/

【Saliency detection】S4Net: Single Stage Salient-Instance Segmentation

Ruochen Fan (Tsinghua University):

Ming-Ming Cheng (Nankai University)*:

Qibin Hou (Nankai University):

Tai-Jiang Mu (Tsinghua University):

Jingdong Wang (Microsoft Research):

Shimin Hu (Tsinghua University): http://cg.cs.tsinghua.edu.cn/prof_hu.htm

【Saliency detection】BASNet: Boundary Aware Salient Object Detection

Xuebin Qin (University of Alberta)*:

Zichen Zhang (University of Alberta):

Chenyang Huang (University of Alberta):

Chao Gao (University of Alberta):

Masood Dehghan (University of Alberta):

Martin Jagersand (University of Alberta):

【Saliency detection】A Mutual Learning Method for Salient Object Detection with intertwined Multi-Supervision

Runmin Wu (Dalian University of Technology ):

Mengyang Feng (Dalian University of Technology):

Wenlong Guan (Dalian University of Technology):

Dong Wang (Dalian University of Technology):

Huchuan Lu (Dalian University of Technology)*: http://ice.dlut.edu.cn/lu/index.html

Errui Ding (Baidu Inc.):

【Saliency detection】A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection

Paul Bergmann (MVTec Software Gmb H)*:

Michael Fauser (MVTec Software Gmb H):

David Sattlegger (MVTec Software Gmb H):

Carsten Steger (MVTec Software Gmb H):

【Saliency detection】Learning to Explore Intrinsic Saliency for Stereoscopic Video

Qiudan ZHANG (City University of Hong Kong):

Xu Wang (Shenzhen University)*:

Shiqi Wang (City U):

Shikai LI (Shenzhen University):

Sam Kwong (City Univeristy of Hong Kong):

Jianmin Jiang (Shenzhen University):

【Saliency detection】Understanding and Visualizing Deep Visual Saliency Models

Sen He (University of Exeter)*:

Hamed Rezazadegan Tavakoli (Aalto University):

Ali Borji (University of Central Florida): http://ilab.usc.edu/borji/

Yang Mi (University of Exeter):

Nicolas Pugeault (Exeter):

【Saliency detection】Shifting More Attention to Video Salient Object Detection

Deng-Ping Fan (Nankai University):

Wenguan Wang (Inception Institute of Artificial Intelligence):

Ming-Ming Cheng (Nankai University)*:

Jianbing Shen (Beijing Institute of Technology): http://cs.bit.edu.cn/shenjianbing/

【Saliency detection】AIRD: Adversarial Learning Framework for Image Repurposing Detection

Ayush Jaiswal (University of Southern California)*:

Yue Wu (USC ISI):

Wael Abd-Almageed (Information Sciences Institute):

Iacopo Masi (University of Southern California):

Prem Natarajan (USC ISI):

【Scene recognition】Bag of Tricks to Train Convolutional Neural Networks for Image Classification

Junyuan Xie (Amazon):

Tong He (Amazon)*:

Zhi Zhang (Amazon):

Hang Zhang (Amazon Inc):

Zhongyue Zhang (Amazon):

Mu Li (Amazon):

【Scene recognition】Learning a Deep Conv Net for Multi-label Classification with Partial Labels

Thibaut Durand (Simon Fraser University)*:

Nazanin Mehrasa (Simon Fraser University):

Greg Mori (Simon Fraser University): http://www.cs.sfu.ca/~mori/

【Scene recognition】Visual Attention Consistency under Image Transforms for Multi-label Image Classification

Hao Guo (University of South Carolina)*:

Kang Zheng (University of South Carolina):

Xiaochuan Fan (University of South Carolina):

Hongkai Yu (University of Texas – Rio Grande Valley):

Song Wang (University of South Carolina):

【Scene recognition】P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification

Bingzhe Wu (Peking University)*:

Shiwan Zhao (IBM Research):

Guangyu Sun (Peking University):

Xiaolu Zhang (Ant Financial Services Group):

Zhong Su (IBM Research):

Caihong Zeng (National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine):

Zhihong Liu (National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine):

【Scene recognition】Mind Your Neighbours: Image Annotation with Metadata Neighbourhood Graph Co-Attention Networks

Junjie Zhang (University of Technology, Sydney):

Qi Wu (University of Adelaide)*:

Jian Zhang (UTS):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Jianfeng Lu (Nanjing University of Science and Technology):

【Scene recognition】Weakly Supervised Complementary Parts Models for Image Classification from the Bottom Up

Weifeng Ge (The University of Hong Kong):

Xiangru Lin (The University of Hong Kong):

Yizhou Yu (Deepwise AI Lab)*: http://i.cs.hku.hk/~yzyu/

【Scene recognition】Unifying Heterogeneous Classifiers with Distillation

Jayakorn Vongkulbhisal (IBM Research)*:

Phongtharin Vinayavekhin (IBM Research):

Marco Visentini-Scarzanella (IBM Research):

【Scene recognition】Tell Me Where I Am: Object-level Scene Context Prediction

Xiaotian Qiao (City University of Hong Kong):

Quanlong Zheng (City University of Hong Kong):

Ying Cao (City University of Hong Kong)*:

Rynson W.H. Lau (City University of Hong Kong):

【Scene recognition】Attentive Relational Networks for Mapping Images to Scene Graphs

Mengshi Qi (Beihang University)*:

Weijian Li (University of Rochester):

Zhengyuan Yang (University of Rochester):

Yunhong Wang (State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China): http://irip.buaa.edu.cn/Chinese.html

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

【Scene recognition】Knowledge-Embedded Routing Network for Scene Graph Generation

Tianshui Chen (Sun Yat-Sen University)*:

Weihao Yu (Sun Yat-sen University):

Riquan Chen (Sun Yat-Sen University):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

【Scene recognition】Learning Deep Compositional Grammatical Architectures for Visual Recognition

Xilai Li (NC State University):

Tianfu Wu (NC State University)*:

Xi Song (None):

【Scene recognition】Spot and Learn: A Maximum-Entropy Image Patch Sampler for Few-Shot Classification

Wen-Hsuan Chu (Carnegie Mellon University)*:

Jing-Cheng Chang (National Taiwan University):

Yu-Jhe Li (National Taiwan University):

Yu-Chiang Frank Wang (National Taiwan University): http://www.citi.sinica.edu.tw/pages/ycwang/index_en.html

【Scene recognition】Mutual Learning of Complementary Networks via Residual Correction for Improving Semi-Supervised Classification

Si Wu (South China University of Technology)*:

Jichang Li (South China University of Technology):

Cheng Liu (City University of Hong Kong):

Zhiwen Yu (South China University of Technology):

Hau San Wong (City University of Hong Kong):

【Scene recognition】Aggregation Cross-Entropy for Sequence Recognition

Zecheng Xie (South China University of Technology):

Yaoxiong Huang (South China University of Technology):

Yuanzhi Zhu (South China University of Technology):

Lianwen Jin (South China University of Technology)*:

Yuliang Liu (South China University of Technology):

Lele Xie (South China University of Technology):

【Scene recognition】Compact Feature Learning for Multi-domain Image Classification

Yajing Liu (USTC):

Xinmei Tian (USTC)*:

Ya Li (IFLYTEK Research):

Zhiwei Xiong (University of Science and Technology of China):

Feng Wu (University of Science and Technology of China):

【Scene recognition】All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification

Weijie Chen (Hikvision Research Institute):

Yuan Zhang (Hikvision Research Institute):

Di Xie (Hikvision Research Institute)*:

Shiliang Pu (Hikvision Research Institute):

【Scene recognition】Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning

Wenbin Li (Nanjing University)*:

Lei Wang (“University of Wollongong, Australia”):

Jinglin Xu (Northwestern Polytechnical University):

Jing Huo (Nanjing University):

Yang Gao (Nanjing University):

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

【Scene recognition】Meta Cleaner: Learning to Hallucinate Clean Representations for Noisy-Labeled Visual Recognition

weihe zhang (Multimedia Laboratory, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Yali Wang (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Yu Qiao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)*: http://mmlab.siat.ac.cn/yuqiao/

【Scene recognition】Mesh Adv: Adversarial Meshes for Visual Recognition

CHAOWEI XIAO (University of Michigan, Ann Arbor):

Dawei Yang (University of Michigan, Ann Arbor)*:

Bo Li (University of Illinois at Urbana–Champaign):

Jia Deng (Princeton University):

mingyan liu (university of Michigan, Ann Arbor):

【Scene recognition】Exploring Context and Visual Pattern of Relationship for Scene Graph Generation

Wenbin Wang (Institute of Computing Technology, Chinese Academy of Science):

Ruiping Wang (ICT, CAS)*:

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

Xilin Chen (China):

【Scene recognition】Explainable and Explicit Visual Reasoning over Scene Graphs

Jiaxin Shi (Tsinghua University)*:

Hanwang Zhang (Nanyang Technological University):

Juanzi Li (Tsinghua University):

【Scene recognition】Topology Reconstruction of Tree-like Structure in Images via Structural Similarity Measure and Dominant Set Clustering

Jianyang Xie (Cixi Institute of Biomedical Engineering, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences):

Yitian Zhao (Cixi Institute of Biomedical Engineering, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences)*:

Yonghuai Liu (Edge Hill University):

Su Pan (Cixi Institute of Biomedical Engineering, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences):

Yifan Zhao (School of Aerospace, Transport and Manufacturing, Cranfield University):

Jun Cheng (Cixi Institute of Biomedical Engineering, Chinese Academy of Sciences):

Yalin Zheng (University of Liverpool):

Jiang Liu (“Chinese Academy of Sciences, China”):

【Scene recognition】Embedding Complementary Deep Networks for Image Classification

Qiuyu Chen (University of North Carolina at Charlotte)*:

Wei Zhang (Fudan University):

Jun Yu (HDU):

Jianping Fan (UNCC):

【Scene recognition】Learning to Explain with Complemental Examples

Atsushi Kanehira (The University of Tokyo)*:

Tatsuya Harada (The University of Tokyo):

【Scene recognition】Learning to Learn Image Classifiers with Visual Analogy

Linjun Zhou (Tsinghua University)*:

Peng Cui (Tsinghua University):

Shiqiang Yang (Tsinghua University):

Wenwu Zhu (Tsinghua Unversity):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Scene recognition】Weakly Supervised Image Classification through Noise Regularization

Mengying Hu (Institute of Computing Technology Chinese Academy of Sciences):

Hu Han (Chinese Academy of Sciences)*:

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

Xilin Chen (China):

【Scene recognition】Translate-to-Recognize Networks for RGB-D Indoor Scene Recognition

Dapeng Du (Nanjing University):

Huiling Wang (Nanjing University):

Kai Zhao (Nanjing University):

Gangshan Wu (Nanjing University):

Limin Wang (Nanjing University)*: http://wanglimin.github.io/

【Scene recognition】Skin-based identification from multispectral image data using CNNs

Takeshi Uemori (Sony Europe Ltd.):

Atsushi Ito (Sony Corporation)*:

Yusuke Moriuchi (Sony Corporation):

Alexander Gatto (Sony Europe Ltd.):

Jun Murayama (Sony Corporation):

【Image retrieval】Generalising Fine-Grained Sketch-Based Image Retrieval

Kaiyue Pang (Queen Mary University of London)*:

Ke Li (BUPT):

Yongxin Yang (University of Edinburgh ):

Honggang Zhang (Beijing University of Posts and Telecommunications):

Yi-Zhe Song (Queen Mary University of London):

Tao Xiang (University of Surrey):

Timothy Hospedales (Edinburgh University): http://homepages.inf.ed.ac.uk/thospeda/

【Image retrieval】Deep Sketch-Shape Hashing with Segmented 3D Stochastic Viewing

Jiaxin Chen (Inception Institute of Artificial Intelligence)*:

Jie Qin (Inception Institute of Artificial Intelligence):

Li Liu (the inception institute of artificial intelligence):

Fan Zhu (Inception Institute of Artificial Intelligence):

Fumin Shen (UESTC):

Jin Xie (Nanjing University of Science and Technology):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Image retrieval】MAN: Moment Alignment Network for Natural Language Moment Retrieval via Iterative Graph Adjustment

Da Zhang (UC Santa Barbara)*:

Xiyang Dai (UMD):

Xin Wang (University of California, Santa Barbara):

Yuan-Fang Wang (UC Santa Barbara):

Larry Davis (University of Maryland): http://www.umiacs.umd.edu/~lsd/

【Image retrieval】Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval

Yale Song (Microsoft)*:

Mohammad Soleymani (University of Southern California):

【Image retrieval】Hybrid-Attention based Decoupled Embedding Learning for Zero-Shot Image Retrieval

Binghui Chen (BUPT)*:

Weihong Deng (Beijing University of Posts and Telecommunications):

【Image retrieval】Doodle to Search: Practical Zero-Shot Sketch-based Image Retrieval

Sounak Dey (Computer Vision Center)*:

Pau Riba (Computer Vision Center):

Anjan Dutta (Computer Vision Center):

Josep Llados (“Computer Vision Center, Barcelona”):

Yi-Zhe Song (Queen Mary University of London):

【Image retrieval】K-Nearest Neighbors Hashing

Xiangyu He (Institute of Automation, Chinese Academy of Sciences)*:

Peisong Wang (Institute of Automation, Chinese Academy of Sciences):

Jian Cheng (“Chinese Academy of Sciences, China”): http://www.nlpr.ia.ac.cn/jcheng/

【Image retrieval】Live Sketch: Query Perturbations for Guided Sketch-based Visual Search

John Collomosse (University of Surrey)*:

Tu Bui (University of Surrey):

Hailin Jin (Adobe Research): http://vision.ucla.edu/~hljin/

【Image retrieval】Distill Hash: Unsupervised Deep Hashing by Distilling Data Pairs

Yang Erkun (Xidian University):

Tongliang Liu (The University of Sydney):

Cheng Deng (Xidian University)*:

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Dacheng Tao (The University of Sydney):

【Image retrieval】End-to-End Supervised Product Quantization for Image Search and Retrieval

Benjamin Klein (Tel Aviv University)*:

Lior Wolf (Tel Aviv University, Israel): http://www.cs.tau.ac.il/~wolf/

【Image retrieval】Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval

Anjan Dutta (Computer Vision Center)*:

Zeynep Akata (University of Amsterdam):

【Image retrieval】Detect-to-Retrieve: Efficient Regional Aggregation for Image Search

Andre Araujo (Google)*:

Marvin Teichmann (University of Cambridge):

Menglong Zhu ():

Jack Sim (Google LLC):

【Image retrieval】A Neurobiological Evaluation Metric for Neural Network Model Search

Nathaniel Blanchard (University of Notre Dame)*:

Jeffery D Kinnison (University of Notre Dame):

Brandon Richard Webster (University of Notre Dame):

Pouya Bashivan (Massachusetts Institute of Technology):

Walter Scheirer (University of Notre Dame):

【Image retrieval】Cross-Modality Personalization for Retrieval

Nils Murrugarra-Llerena (University of Pittsburgh)*:

Adriana Kovashka (University of Pittsburgh):

【Image retrieval】Composing Text and Image for Image Retrieval – An Empirical Odyssey

Nam Vo (Georgia Institute of Technology)*:

Lu Jiang (Google):

Chen Sun (Google):

Kevin Murphy (Google):

Li-Jia Li (Stanford):

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

James Hays (Georgia Institute of Technology, USA): http://www.cs.brown.edu/~hays/

【Image retrieval】Deep Incremental Hashing Network for Efficient Image Retrieval

Dayan Wu (Institute of Information Engineering, Chinese Academy of Sciences)*:

Qi Dai (Microsoft Research):

Jing Liu (Institute of Information Engineering, Chinese Academy of Sciences):

Bo Li ( Institute of Information Engineering, Chinese Academy of Sciences):

Weiping Wang (Institute of Information Engineering, CAS, China):

【Image retrieval】Dual Dense Encoding for Zero-Example Video Retrieval

Jianfeng Dong (Zhejiang Gongshang University):

Xirong Li (Renmin University of China)*:

Chaoxi Xu (Renmin University of China):

Shouling Ji (Zhejiang University):

Yuan He (Alibaba Group ):

Gang Yang (Renmin University of China):

Xun Wang (Zhejiang Gongshang University):

【Image retrieval】Explore-Exploit Graph Traversal for Image Retrieval

Guangwei Yu (Layer6.ai)*:

Chundi Liu (Layer6.ai):

Cheng Chang (Layer6.ai):

Maksims Volkovs (Layer6 AI):

【Image retrieval】Weakly Supervised Deep Image Hashing through Tag Embeddings

Vijetha R Gattupalli (Arizona State University)*:

Yaoxin Zhuo (Arizona State University):

baoxin Li (Arizona State University):

【Image retrieval】Deep Supervised Cross-modal Retrieval

Liangli Zhen (Institute of High Performance Computing, A*STAR):

Peng Hu (Sichuan University):

Xu Wang (Sichuan University):

Dezhong Peng (Sichuan University)*:

【Image retrieval】Complete the Look: Scene-based Complementary Product Recommendation

Wang-Cheng Kang (UC San Diego)*:

Eric Kim (Pinterest):

Jure Leskovec (Stanford):

Charles Rosenberg (Pinterest):

Julian Mc Auley (UCSD):

【Image retrieval】Learning Binary Code for Personalized Fashion Recommendation

Zhi Lu (University of Electronic Science and Technology of China):

Yang Hu (University of Electronic Science and Technology of China)*:

Yunchao Jiang (University of Electronic Science and Technology of China):

Yan Chen (University of Electronic Science and Technology of China):

Bing Zeng (University of Electronic Science and Technology of China):

【Image retrieval】R2GAN: Cross-modal Recipe Retrieval with Generative Adversarial Network

Bin Zhu (City University of Hong Kong)*:

Jingjing Chen (City University of Hong Kong):

Yanbin Hao (City University of Hong Kong):

Chong-Wah Ngo (City University of Hong Kong):

【Image retrieval】Weakly Supervised Video Moment Retrieval From Text Queries

Niluthpol c Mithun (UC Riverside)*:

Sujoy Paul (UC Riverside):

Amit Roy-Chowdhury (University of California, Riverside, USA ): http://vcg.engr.ucr.edu/

【Image retrieval】Deep Spherical Hashing

Sepehr Eghbali (University of Waterloo)*:

Ladan Tahvildari (University of Waterloo):

【Image retrieval】Context-Aware Visual Compatibility Prediction

Guillem Cucurull (Element AI)*:

Perouz Taslakian (Element AI):

David Vazquez (Element AI):

【3D analysis】Unsupervised Learning of Consensus Maximization for 3D Vision Problems

Thomas Probst (ETH Zurich)*:

Danda Pani Paudel (ETH Zürich):

Ajad Chhatkuli (ETH Zurich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【3D analysis】Strand-accurate Multi-view Hair Capture

Giljoo Nam (KAIST)*:

Chenglei Wu (Facebook Reality Labs):

Min H. Kim (KAIST):

Yaser Sheikh (Facebook Reality Labs): http://www.cs.cmu.edu/~yaser/

【3D analysis】Pushing the Boundaries of View Extrapolation with Multiplane Images

Pratul Srinivasan (UC Berkeley)*:

Richard Tucker (Google):

Jonathan T Barron (Google Research):

Ravi Ramamoorthi (University of California San Diego):

Ren Ng (UC Berkeley):

Noah Snavely (Cornell University and Google AI): http://www.cs.cornell.edu/~snavely/

【3D analysis】Coordinate-Free Carlsson-Weinshall Duality and Relative Multi-View Geometry

Matthew Trager (NYU)*:

Martial Hebert (Carnegie Mellon University): http://www.cs.cmu.edu/~hebert/

Jean Ponce (Inria): http://www.di.ens.fr/willow/

【3D analysis】Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image

Xiaoguang Han (Shenzhen Research Institute of Big Data, the Chinese University of Hong Kong (Shenzhen))*:

Zhaoxuan Zhang (Dalian University of Technology, Shenzhen Research Institute of Big Data):

Dong Du (University of Science and Technology of China, Shenzhen Research Institute of Big Data):

Mingdai Yang (Chinese University of Hong Kong, Shenzhen):

Jingming Yu (Alibaba):

Pan Pan (Alibaba Group):

Xin Yang (Dalian University of Technology):

Ligang Liu (University of Science and Technology of China):

Zixiang Xiong (Texas A&M University):

Shuguang Cui (The Chinese University of Hong Kong, Shenzhen ):

【3D analysis】Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction

Chen-Hsuan Lin (Carnegie Mellon University)*:

Bryan Russell (Adobe Research):

Oliver Wang (Adobe Systems Inc):

Vladimir Kim (Adobe):

Simon Lucey (CMU): http://www.cs.cmu.edu/~slucey/

Matthew Fisher (Adobe Research):

Eli Shechtman (Adobe Research, US): http://www.adobe.com/technology/people/seattle/eli-shechtman.html

【3D analysis】3D Point-Capsule Networks

Tolga Birdal (TU Munich)*:

Yong Heng Zhao (University of Padova):

Haowen Deng (Technical University of Munich):

Federico Tombari (Technical University of Munich, Germany): http://vision.deis.unibo.it/fede/

【3D analysis】GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving

Buyu LI (The Chinese University of Hong Kong)*:

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Lu Sheng (The Chinese University of Hong Kong):

Xingyu ZENG (Sense Time Group Limited):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【3D analysis】Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding

Zehao Yu (Shanghai Tech University):

Jia Zheng (Shanghai Tech University):

Dongze Lian (Shanghaitech University):

Zihan Zhou (Penn State University):

Shenghua Gao (Shanghaitech University)*:

【3D analysis】Horizon Net: Learning Room Layout with 1D Representation and Pano Stretch Data Augmentation

Cheng Sun (National Tsing Hua University)*:

Chi-Wei Hsiao (National Tsing Hua University):

Min Sun (NTHU): http://aliensunmin.github.io/

Hwann-Tzong Chen (National Tsing Hua University): http://www.cs.nthu.edu.tw/~htchen/

【3D analysis】Deep Relational Reasoning Network for Monocular 3D Object Detection

Lijie Liu (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Chunjing Xu (Huawei Noah’s Ark Lab):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【3D analysis】Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction

Yifei Shi (National University of Defense Technology):

Angel X Chang (Eloquent Labs):

Manolis Savva (Simon Fraser University):

Zhenlun Wu (Princeton University):

Kai Xu (National University of Defense Technology)*:

【3D analysis】Scene Graph Generation with External Knowledge and Image Reconstruction

Jiuxiang Gu (Nanyang Technological University)*:

Handong Zhao (Adobe Research):

Zhe Lin (Adobe Research): http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Sheng Li (University of Georgia):

Jianfei Cai (Nanyang Technological University): http://www3.ntu.edu.sg/home/asjfcai/

Mingyang Ling (Google Cloud AI):

【3D analysis】Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition

Zizhao Zhang (University of Florida)*:

Adriana Romero (FAIR):

Matthew Muckley (New York University):

Pascal Vincent (Facebook FAIR & MILA Université de Montréal):

Lin Yang (University of Florida):

Michal Drozdzal (FAIR):

【3D analysis】Biologically-Constrained Graphs for Global Connectomics Reconstruction

Brian Matejek (Harvard University )*:

Daniel Haehn (Harvard University):

Haidong Zhu (Tsinghua University):

Donglai Wei (Harvard/SEAS):

Toufiq Parag (Harvard University):

Hanspeter Pfister (Harvard University):

【3D analysis】Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling

Jiancheng YANG (Shanghai Jiao Tong University):

Qiang Zhang (Shanghai Jiao Tong University):

Bingbing Ni (Shanghai Jiao Tong University)*:

Linguo Li (Shanghai Jiao Tong University):

Jinxian Liu (Shanghai Jiao Tong University):

Mengdie Zhou (Shanghai Jiao Tong University):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【3D analysis】Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition

Lin Xu (Institute of Advanced Artificial Intelligence (IAAI))*:

Han Sun (Institute of Advanced Artificial Intelligence (IAAI)):

Yuai Liu (Institute of Advanced Artificial Intelligence (IAAI)):

【3D analysis】Dense Fusion: 6D Object Pose Estimation by Iterative Dense Fusion

Chen Wang (Shanghai Jiao Tong University)*:

Danfei Xu (Stanford University):

Yuke Zhu (Stanford University):

Roberto Martín-Martín (Stanford University):

Cewu Lu (Shanghai Jiao Tong University): http://mvig.sjtu.edu.cn/

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

【3D analysis】Du La-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama

Shang-Ta Yang (National Tsing Hua University)*:

Fu-En Wang (National Tsing Hua University):

Chi-Han Peng (KAUST):

Peter Wonka (KAUST):

Hung-Kuo Chu (National Tsing Hua University):

Min Sun (NTHU): http://aliensunmin.github.io/

【3D analysis】What Do Single-view 3D Reconstruction Networks Learn?

Maxim Tatarchenko (Freiburg)*:

Stephan R Richter (Intel Labs):

Rene Ranftl (Intel Labs):

Zhuwen Li (Pony AI):

Vladlen Koltun (Intel Labs): http://vladlen.info/publications/

Thomas Brox (University of Freiburg): http://lmb.informatik.uni-freiburg.de/people/brox/index.en.html

【3D analysis】Deep Voxels: Learning Persistent 3D Feature Embeddings

Vincent Sitzmann (Stanford University)*:

Justus Thies (Technical University of Munich):

Felix Heide (Princeton University):

Matthias Niessner (Technical University of Munich): http://niessnerlab.org/publications.html

Gordon Wetzstein (Stanford University):

Michael Zollhoefer (Stanford University):

【3D analysis】Scan2CAD: Learning CAD Model Alignment in RGB-D Scans

Armen Avetisyan (Technical University of Munich)*:

Manuel Dahnert (Technical University of Munich):

Angela Dai (Technical University of Munich):

Manolis Savva (Simon Fraser University):

Angel X Chang (Eloquent Labs):

Matthias Niessner (Technical University of Munich): http://niessnerlab.org/publications.html

【3D analysis】Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

He Wang (Stanford University):

Srinath Sridhar (Stanford University)*:

Jingwei Huang (Stanford University):

Julien Valentin (Google):

Shuran Song (Princeton):

Leonidas Guibas (Stanford University):

【3D analysis】Surface Reconstruction from Normals: A Robust DGP-based Discontinuity Preservation Approach

Wuyuan Xie (Shenzhen University):

Miaohui Wang (Shenzhen University)*:

Jing Qin (The Hong Kong Polytechnic University):

Mingqiang Wei (Nanjing University of Aeronautics and Astronautics):

Jianmin Jiang (Shenzhen University):

【3D analysis】Synthesizing 3D Shapes from Unannotated Image Collections using Multi-projection Generative Adversarial Networks

Xiao Li (University of Science and Technology of China)*:

Yue Dong (Microsoft Research Asia):

Pieter Peers (College of William & Mary):

Xin Tong (Microsoft):

【3D analysis】3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans

Ji Hou (Technical University of Munich):

Angela Dai (Technical University of Munich):

Matthias Niessner (Technical University of Munich)*: http://niessnerlab.org/publications.html

【3D analysis】Plane RCNN: 3D Plane Detection and Reconstruction from a Single View

Chen Liu (Washington University in St. Louis)*:

Kihwan Kim (NVIDIA):

Jinwei Gu (NVIDIA):

Yasutaka Furukawa (Simon Fraser University):

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【3D analysis】Occupancy Networks: Learning 3D Reconstruction in Function Space

Lars M Mescheder (MPI-IS and University of Tuebingen)*:

Michael Oechsle (MPI-IS, University of Tuebingen and ETAS Gmb H):

Michael Niemeyer (MPI-IS and University of Tuebingen):

Sebastian Nowozin (Google AI Berlin): http://www.nowozin.net/sebastian/

Andreas Geiger (MPI-IS and University of Tuebingen):

【3D analysis】3D Shape Reconstruction from Images in the Frequency Domain

Weichao Shen (Beijing Institute of Technology)*:

Yuwei WU (Beijing Institute of Technology (BIT), China):

Yunde Jia (Beijing Institute of Technology):

【3D analysis】Convolutional Mesh Regression for Single-Image Human Shape Reconstruction

Nikos Kolotouros (University of Pennsylvania)*:

Georgios Pavlakos (University of Pennsylvania):

Kostas Daniilidis (University of Pennsylvania):

【3D analysis】Cross-atlas Convolution for Parameterization Invariant Learning on Textured Mesh Surface

Shiwei Li (HKUST)*:

Zixin Luo (HKUST):

Mingmin Zhen (Hong Kong University of Science and Technology):

Yao Yao (The Hong Kong University of Science and Technology):

Tianwei Shen (HKUST):

Tian Fang (Altizure):

Long Quan (Hong Kong University of Science and Technology): http://visgraph.cs.ust.hk/index.html

【3D analysis】Deep Surface Normal Estimation with Hierarchical RGB-D Fusion

Jin Zeng (Sense Time Research)*:

Yanfeng Tong (Beijing Institute of Technology):

Yunmu Huang (Sense Time Research):

Qiong Yan (Sense Time Group Limited):

Wenxiu Sun (Sense Time Research):

Jing Chen (Beijing Institute of Technology):

Yongtian Wang (Beijing Institute of Technology):

【3D analysis】Noise-Aware Unsupervised Deep Lidar-Stereo Fusion

Xuelian Cheng (Australian National University):

Yiran Zhong (Australian National University):

Yuchao Dai (Northwestern Polytechnical University)*:

Pan Ji (NEC Laboratories America):

HONGDONG LI (Australian National University, Australia):

【3D analysis】IGE-Net: Inverse Graphics Energy Networks\\for Human Pose Estimation and Single-View Reconstruction

Dominic Jack (Queensland University of Technology)*:

Frederic Maire (Queensland University of Technology):

SAREH SHIRAZI (Queensland University of Technology, Australia):

Anders Eriksson (Queensland University of Technology):

【3D analysis】RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion

Jie Li (Nanjing University of Science and Technology)*:

Yu Liu (The University of Adelaide):

Dong Gong (The University of Adelaide):

Qinfeng Shi (University of Adelaide): https://cs.adelaide.edu.au/~javen/

Xia Yuan (Nanjing University of Science and Technology):

Chunxia Zhao (Nanjing University of Science and Technology):

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

【3D analysis】Hyperspectral Image Reconstruction using a Spectral Regularization Prior

Lizhi Wang (Beijing Institute of Technology):

Chen Sun (Beijing Institute of Technology):

Ying Fu (Beijing Institute of Technology):

Min H. Kim (KAIST):

Hua Huang (Beijing Institute of Technology)*:

【3D analysis】ABC: A Big CAD Model Dataset For Geometric Deep Learning

Sebastian Koch (TUB)*:

Albert Matveev (Skoltech):

Zhongshi Jiang (New York University):

Francis Williams (New York University):

Alexey Artemov (Skoltech):

Evgeny Burnaev (Skoltech):

Marc Alexa (TUB):

Denis Zorin (New York University):

Daniele Panozzo (NYU):

【3D analysis】Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction

Yi Wei (Tsinghua University):

Shaohui Liu (Tsinghua University):

Wang Zhao (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

【3D analysis】Radial Distortion Triangulation

Zuzana Kukelova (Czech Technical University in Prague)*:

Viktor Larsson (ETH Zurich):

【3D analysis】Robust Point Cloud Reconstruction of Large-Scale Outdoor Scenes

Ziquan Lan (NUS)*:

Zi Jian Yew (National University of Singapore):

Gim Hee Lee (National University of SIngapore): https://sites.google.com/site/gimheelee/home/publications

【3D analysis】Minimal Solvers for Mini-Loop Closures in 3D Multi-Scan Alignment

Pedro Miraldo (KTH Royal Institute of Technology, Stockholm)*:

Surojit Saha (University of Utah):

Srikumar Ramalingam (University of Utah):

【3D analysis】Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres

Shuai Liao (University of Amsterdam)*:

Stratis Gavves (University of Amsterdam):

Cees Snoek (University of Amsterdam):

【3D analysis】Learning View Priors for Single-view 3D Reconstruction

Hiroharu Kato (The University of Tokyo)*:

Tatsuya Harada (The University of Tokyo):

【3D analysis】SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception

Dinesh Bharadia (University of California San Diego):

Tara Javidi (University of California San Diego):

Gaurav Bansal (Airbus Labs):

Rui Guo (Toyota Info Technology Center USA):

Aman Raj (University of California San Diego):

Samuel Sunarjo (University of California, San Diego):

Yongxi Lu (Unviersity of California, San Diego):

Yue Meng (University of California San Diego)*:

【3D analysis】Deep Geometric Prior for Surface Reconstruction

Francis Williams (New York University)*:

Teseo Schneider (NYU Courant Institute):

Claudio Silva (NYU):

Denis Zorin (New York University):

Joan Bruna (Courant Institute of Mathematical Sciences, NYU, USA):

Daniele Panozzo (NYU):

【3D analysis】Divergence Prior and Vessel-tree Reconstruction

Zhongwen Zhang (University of Western Ontario):

Dmitrii Marin (University of Waterloo)*:

Egor Chesakov (University of Western Ontario (former Ph D student)):

Yuri Boykov (University of Waterloo): http://www.csd.uwo.ca/~yuri/

Maria Drangova (Robarts Research Institute):

Marc Moreno Maza (University of Western Ontario):

【3D analysis】Inverse Procedural Modeling of Knitwear

Elena Trunz (University of Bonn)*:

Sebastian Merzbach (University of Bonn):

Jonathan Klein (University of Bonn):

Thomas Schulze (University of Bonn):

Michael Weinmann (University of Bonn):

Reinhard Klein (University of Bonn):

【3D analysis】Scene Code: Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations

Shuaifeng Zhi (Imperial College London)*:

Michael Bloesch (Imperial College London):

Stefan Leutenegger (Imperial College London): http://wp.doc.ic.ac.uk/sleutene/

Andrew Davison (Imperial College London):

【3D analysis】Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments

Xueting Li (University of California, Merced)*:

Sifei Liu (NVIDIA):

Kihwan Kim (NVIDIA):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

Xiaolong Wang (CMU):

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【PointCloud analysis】Structural Point Cloud Decoder

Lyne P Tchapmi (Stanford University)*:

Hamid Rezatofighi (University of Adelaide):

Vineet S Kosaraju (Stanford Vision & Learning Lab):

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

【PointCloud analysis】Spherical Fractal Convolution Neural Networks for Point Cloud Recognition

Yongming Rao (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【PointCloud analysis】Flow Net3D: Learning Scene Flow in 3D Point Clouds

Xingyu Liu (Stanford University)*:

Charles R. Qi (Facebook AI Research):

Leonidas Guibas (Stanford University):

【PointCloud analysis】Point RCNN: 3D Object Proposal Generation and Detection from Point Cloud

Shaoshuai Shi (The Chinese University of Hong Kong)*:

Hongsheng Li (Chinese University of Hong Kong):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【PointCloud analysis】Part Net: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding

Kaichun Mo (Stanford)*:

Shilin Zhu (UCSD):

Angel X Chang (Eloquent Labs):

Li Yi (Stanford):

Subarna Tripathi (Intel AI Lab):

Leonidas Guibas (Stanford University):

Hao Su (UCSD):

【PointCloud analysis】SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences

Huu Minh Le (Queensland University of Technology)*:

Thanh-Toan Do (The University of Liverpool):

Tuan NA Hoang (Singapore University of Technology and Design):

Ngai-Man Cheung (Singapore University of Technology and Design):

【PointCloud analysis】Structural Relational Reasoning of Point Clouds

Yueqi Duan (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Yu Zheng (Tsinghua University):

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【PointCloud analysis】Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN

Shiyi Lan (University of Maryland)*:

Ruichi Yu (University of Maryland, College Park):

Gang Yu (Face++):

Larry Davis (University of Maryland): http://www.umiacs.umd.edu/~lsd/

【PointCloud analysis】3DN: 3D Deformation Network

Weiyue Wang (USC)*:

Duygu Ceylan (Adobe Research):

Radomir Mech (Adobe Systems Incorporated):

Ulrich Neumann (USC): https://graphics.usc.edu/cgit/un.html

【PointCloud analysis】3D Local Features for Direct Pairwise Registration

Tolga Birdal (TU Munich)*:

Haowen Deng (Technical University of Munich):

Slobodan Ilic (TUM):

【PointCloud analysis】SPLFlow Net: Sparse Permutohedral Lattice Flow Net for Scene Flow Estimation on Large-scale Point Clouds

Xiuye Gu (Stanford University)*:

Chongruo Wu (UC Davis):

Yijie Wang (Tu Simple):

Panqu Wang (Tu Simple):

Yong Jae Lee (University of California, Davis):

【PointCloud analysis】Supervised Fitting of Geometric Primitives to 3D Point Clouds

Lingxiao Li (Stanford University)*:

Minhyuk Sung (Stanford University):

Anastasia Dubrovina (Stanford):

Li Yi (Stanford):

Leonidas Guibas (Stanford University):

【PointCloud analysis】GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud

Li Yi (Stanford)*:

Wang Zhao (Tsinghua University):

He Wang (Stanford University):

Minhyuk Sung (Stanford University):

Leonidas Guibas (Stanford University):

【PointCloud analysis】Associatively Segmenting Instances and Semantics in Point Clouds

Xinlong Wang (Tongji University)*:

Shu Liu (Tencent):

Xiaoyong Shen (Tencent):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【PointCloud analysis】LP-3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networks

Sudhakar Kumawat (Indian Institute of Technology Gandhinagar)*:

Shanmuganathan Raman (Indian Institute of Technology (IIT) Gandhinagar):

【PointCloud analysis】Cluster Net: Deep Hierarchical Cluster Network with Rigorously Rotation-Invariant Representation for Point Cloud Recognition

Chao Chen (Sun Yat-sen University):

Guanbin Li (Sun Yat-sen University)*:

Ruijia Xu (Sun Yat-sen University):

Tianshui Chen (Sun Yat-Sen University):

Meng Wang (Hefei University of Technology):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

【PointCloud analysis】The Perfect Match: 3D Point Cloud Matching with Smoothed Densities

Zan Gojcic (ETH Zürich)*:

Zhou Caifa (IGP, ETH Zurich):

Jan Dirk Wegner (ETH Zurich):

Andreas Wieser (ETH Zürich):

【PointCloud analysis】Point Web: Enhancing Local Neighborhood Features for Point Cloud Processing

Hengshuang Zhao (The Chinese University of Hong Kong)*:

Li Jiang (The Chinese University of Hong Kong):

Chi-Wing Fu (The Chinese University of Hong Kong):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【PointCloud analysis】Scan2Mesh: From Unstructured Range Scans to 3D Meshes

Angela Dai (Technical University of Munich)*:

Matthias Niessner (Technical University of Munich): http://niessnerlab.org/publications.html

【PointCloud analysis】Patch-based Progressive 3D Point Set Upsampling

Yifan Wang (ETH Zurich)*:

Shihao Wu (ETH Zurich):

Hui Huang (Shenzhen University): http://vcc.szu.edu.cn/~huihuang

Daniel Cohen-Or (Tel Aviv University):

Olga Sorkine-Hornung (ETH Zurich):

【PointCloud analysis】Point Net LK: Robust & Efficient Point Cloud Registration using Point Net

Hunter M Goforth (Carnegie Mellon University)*:

Arun Srivatsan Rangaprasad (Carnegie Mellon University):

Yasuhiro Aoki (Fujitsu Laboratries Ltd.):

Simon Lucey (CMU): http://www.cs.cmu.edu/~slucey/

【PointCloud analysis】CNN: Annularly Convolutional Neural Networks on Point Clouds

Artem Komarichev (Wayne State University):

Zichun Zhong (Wayne State University)*:

Jing Hua (Wayne State University):

【PointCloud analysis】Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning

loic landrieu (IGN)*:

Mohamed Boussaha (IGN):

【PointCloud analysis】Point Flow Net: Learning Representations for Rigid Motion Estimation from Point Clouds

Aseem Behl (MPI-IS and University of Tuebingen)*:

Despoina Paschalidou (MPI-IS Tuebingen ):

Simon Donné (MPI-IS and University of Tübingen):

Andreas Geiger (MPI-IS and University of Tuebingen):

【PointCloud analysis】Geo Net: Deep Geodesic Networks for Point Cloud Analysis

Tong He (UCLA)*:

Haibin Huang (Face++ (Megvii)):

Li Yi (Stanford):

Yuqian Zhou (UIUC):

QIHAO WU (Face++ (Megvii)):

jue wang (Face++ (Megvii)):

Stefano Soatto (UCLA): http://vision.ucla.edu/projects.html

【PointCloud analysis】Generating 3D Adversarial Point Clouds

Chong Xiang (Shanghai Jiao Tong University)*:

Charles R. Qi (Facebook AI Research):

Bo Li (University of Illinois at Urbana–Champaign):

【PointCloud analysis】Joint Semantic-Instance Segmentation of 3D Point Clouds Using Multi-Set Label Conditional Random Fields

Quang-Hieu Pham (Singapore University of Technology and Design)*:

Binh-Son Hua (The University of Tokyo):

Thanh Nguyen (Deakin University, Australia):

Gemma Roig (MIT):

Sai-Kit Yeung (Hong Kong University of Science and Technology): http://www.saikit.org/

【PointCloud analysis】Relation-Shape Convolutional Neural Network for Point Cloud Analysis

Yongcheng Liu (Institute of Automation, Chinese Academy of Sciences)*:

Bin Fan (Institute of Automation, Chinese Academy of Sciences, China):

SHIMING XIANG (Chinese Academy of Sciences, China):

Chunhong Pan (Institute of Automation, Chinese Academy of Sciences): http://people.gucas.ac.cn/~panchunhong

【PointCloud analysis】Point Conv: Deep Convolutional Networks on 3D Point Clouds

Wenxuan Wu (Oregon State University)*:

Zhongang Qi (Oregon State University):

Li Fuxin (Oregon State University):

【PointCloud analysis】Octree guided CNN with Spherical Kernels for 3D Point Clouds

Huan Lei (The University of Western Australia)*:

Naveed Akhtar (The University of Western Australia):

Ajmal Mian (University of Western Australia):

【PointCloud analysis】Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks

Yizhak Ben-Shabat (Technion)*:

Anath Fischer (Technion):

Michael Lindenbaum (Technion):

【PointCloud analysis】Graph Attention Convolution for Point Cloud Segmentation

Lei Wang (Wuhan University)*:

Yuchun Huang (Wuhan University):

Yaolin Hou (Wuhan University):

Shenman Zhang (Wuhan University):

Jie Shan (Purdue):

【PointCloud analysis】Self-supervised Fitting of Articulated Meshes to Point Clouds

Chun-Liang Li (Carnegie Mellon University)*:

Tomas Simon (Carnegie Mellon University):

Jason Saragih (Oculus):

Barnabas Poczos ( Carnegie Mellon University):

Yaser Sheikh (Facebook Reality Labs): http://www.cs.cmu.edu/~yaser/

【PointCloud analysis】Path-Invariant Map Networks

Zaiwei Zhang (University of Texas at Austin):

Zhenxiao Liang (The University of Texas at Austin):

Lemeng Wu (The University of Texas at Austin):

Xiaowei Zhou (Zhejiang Univ., China):

Qixing Huang (The University of Texas at Austin)*:

【PointCloud analysis】Filter Reg: Robust and Efficient Probabilistic Point-Set Registration using Gaussian Filter and Twist Parameterization

Wei Gao (MIT)*:

Russ Tedrake (MIT):

【PointCloud analysis】PCAN:Learning Attention Map Using Contextual Information for Point Cloud Based Retrieval

Chunxia Xiao (Wuhan University)*:

Wenxiao Zhang (Wuhan University):

【PointCloud analysis】Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds

Zihao Liu (Florida International University)*:

Xiaowei Xu (University of Notre Dame):

Tao Liu (Florida International University):

Qi Liu (Florida International University ):

Yanzhi Wang (Northeastern University):

Yiyu Shi (University of Notre Dame):

Wujie Wen (Florida International University):

Meiping Huang (Guangdong General Hospital):

Haiyun Yuan (Guangdong General Hospital):

Jian Zhuang (Guangdong General Hospital):

【PointCloud analysis】Point Pillars: Fast Encoders for 3D Object Detection from Point Clouds

Alex H Lang (nu Tonomy: an APTIV company)*:

Sourabh Vora (nu Tonomy: an APTIV company):

Holger Caesar (nu Tonomy: an APTIV company):

Lubing Zhou (nu Tonomy: an APTIV company):

Jiong Yang (nu Tonomy: an APTIV company):

Oscar Beijbom (nu Tonomy: an APTIV company):

【Auto driver】Apollo Car3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

Xibin Song (Baidu):

Peng Wang (Baidu USA LLC.)*:

Dingfu Zhou (Baidu):

Rui Zhu (UCSD):

chenye guan (baidu):

Yuchao Dai (Northwestern Polytechnical University):

Hao Su (UCSD):

HONGDONG LI (Australian National University, Australia):

Yang Ruigang (Baidu):

【Auto driver】L3-Net: Towards Learning based Li DAR Localization for Autonomous Driving

Weixin Lu (Baidu ADU):

Yao Zhou (Baidu ADU):

Guowei Wan (Baidu Company):

Shenhua Hou (Baidu ADU):

Shiyu Song (Baidu ADU)*:

【Auto driver】Image-based Navigation using Visual Features and Map

Janine D Thoma (ETH Zurich)*:

Danda Pani Paudel (ETH Zürich):

Ajad Chhatkuli (ETH Zurich):

Thomas Probst (ETH Zurich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Auto driver】Stereo R-CNN based 3D Object Detection for Autonomous Driving

Peiliang LI (HKUST Robotics Institute)*:

Xiaozhi Chen (DJI):

Shaojie Shen (HKUST): http://uav.ust.hk/

【Auto driver】Pseudo-Li DAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Yan Wang (Cornell University)*:

Wei-Lun Chao (Cornell University):

Divyansh Garg (Cornell University):

Bharath Hariharan (Cornell University):

Mark Campbell (Cornell University):

Kilian Weinberger (Cornell University):

【Auto driver】Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions

Benjamin Sapp (Google)*:

Joey Hong (Caltech):

James Philbin (Zoox):

【Auto driver】A Parametric Top-View Representation of Complex Road Scenes

Ziyan Wang (CMU):

Buyu Liu (NEC Labs):

Samuel Schulter (NEC Labs)*:

Manmohan Chandraker (UC San Diego): http://cseweb.ucsd.edu/~mkchandraker/

【Auto driver】Improved Road Connectivity by Joint Learning of Orientation and Segmentation

Anil Batra (IIIT)*:

Suriya Singh (IIIT, Mila):

Guan Pang (Facebook):

Saikat Basu (Facebook):

C.V. Jawahar (IIIT-Hyderabad):

Manohar Paluri (Facebook):

【Auto driver】Grounding Human-to-Vehicle Advice for Self-driving Vehicles

Jinkyu Kim (UC Berkeley)*:

Teruhisa Misu (Honda Research Institute USA):

Yi-Ting Chen (Honda Research Institute USA):

Ashish Tawari (Honda Research Institute):

John F Canny (UC Berkeley):

【Auto driver】Multi-Step Prediction of Occupancy Grid Maps with Recurrent Neural Networks

Nima Mohajerin (Huawei Noah’s Ark)*:

Mohsen Rohani (Huawei Noah’s Ark):

【Auto driver】Sim-Real Joint Reinforcement Transfer for 3D Indoor Navigation

Fengda Zhu (UTS)*:

Linchao Zhu (University of Technology, Sydney):

Yi Yang (UTS): http://www.cs.cmu.edu/~yiyang/

【Auto driver】Convolutional Spatial Fusion for Multi-Agent Trajectory Prediction

Tianyang Zhao (Peking University)*:

Yifei Xu (UCLA):

Mathew Monfort (i See):

Wongun Choi (i See):

Chris Baker (i See):

Yibiao Zhao (i See):

Yizhou Wang (PKU):

Ying Nian Wu (University of California, Los Angeles):

【Auto driver】Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention

Khanh X Nguyen (University of Maryland)*:

Debadeepta Dey (Microsoft):

Chris Brockett (Microsoft):

Bill Dolan (Microsoft):

【Auto driver】Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments

Howard Chen (Cornell)*:

Alane Suhr (Cornell University):

Dipendra Misra (Cornell University):

Noah Snavely (Cornell University and Google AI): http://www.cs.cornell.edu/~snavely/

Yoav Artzi (Cornell University):

【Auto driver】In Defense of Pre-Trained Image Net Architectures for Real-Time Semantic Segmentation of Road-driving Images

Marin Oršić (UNIZG-FER)*:

Ivan Krešo (UNIZG-FER):

Petra Bevandić (Faculty of Electrical Engineering and Computing):

Sinisa Segvic (Uni Zg-FER):

【Auto driver】Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks

Stephen L James (Imperial College London)*:

Paul Wohlhart (Google X):

Raia Hadsell (Google Deepmind):

Julian Ibarz (Google):

Alex Irpan (Google):

Dmitry Kalashnikov (Google Inc.):

Sergey Levine (Google):

Mrinal Kalakrishnan (X):

Konstantinos Bousmalis (Deep Mind):

【Auto driver】Laser Net: An Efficient Probabilistic 3D Object Detector for Autonomous Driving

Ankit Laddha (Uber)*:

Greg Meyer (Uber):

Carl Wellington (Uber):

Carlos Vallespi-Gonzalez (Uber):

Eric Kee (Uber ATG):

【Feature matching】Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation

Jaime Spencer Martin (University of Surrey)*:

Richard Bowden (University of Surrey):

Simon Hadfield (University of Surrey):

【Feature matching】Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks

Dinesh Reddy Narapureddy (Carnegie mellon university)*:

Minh P Vo (Facebook):

Srinivasa G Narasimhan (Carnegie Mellon University):

【Feature matching】Li FF: Light Field Features in Scale and Depth

Donald G Dansereau (University of Sydney)*:

Bernd Girod (Stanford University):

Gordon Wetzstein (Stanford University):

【Feature matching】D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

Mihai Dusmanu (ETH Zurich)*:

Ignacio ROCCO (Inria):

Tomas Pajdla (Czech Technical University in Prague):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

Josef Sivic (INRIA):

Akihiko Torii (Tokyo Institute of Technology, Japan):

Torsten Sattler (Chalmers University of Technology):

【Feature matching】Explicit Spatial Encoding for Deep Local Descriptors

Arun Mukundan (CTU in Prague)*:

Giorgos Tolias (Vision Recognition Group, Czech Technical University in Prague):

Ondrej Chum (Vision Recognition Group, Czech Technical University in Prague): http://cmp.felk.cvut.cz/~chum/

【Feature matching】Man Tra-Net: Manipulation Tracing Network For Detection And Localization of Image Forgeries With Anomalous Features

Yue Wu (USC ISI)*:

Wael Abd-Almageed (Information Sciences Institute):

Prem Natarajan (USC ISI):

【Feature matching】Speed Invariant Time Surface for Learning to Detect Corner Points with Event-Based Cameras

Jacques Manderscheid (PROPHESEE):

Amos Sironi (PROPHESEE)*:

Nicolas Bourdis (PROPHESEE):

Davide Migliore (PROPHESEE):

Vincent Lepetit (L’Universite de Bordeaux): http://cvlabwww.epfl.ch/~lepetit/

【Feature matching】SOSNet: Second Order Similarity Regularization for Local Descriptor Learning

yurun tian (National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences):

Xin Yu (Australian National University):

Bin Fan (Institute of Automation, Chinese Academy of Sciences, China)*:

Fuchao Wu (National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences):

Huub Heijnen (Scape Technologies):

Vassileios Balntas (Scape Technologies):

【Motion estimation】BAD SLAM: Bundle Adjusted Direct RGB-D SLAM

Thomas Schöps (ETH Zurich)*:

Torsten Sattler (Chalmers University of Technology):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

【Motion estimation】Revealing Scenes by Inverting Structure from Motion Reconstructions

Francesco Pittaluga (University of Florida)*:

Sanjeev J Koppal (University of Florida):

Sing Bing Kang (Microsoft Research): http://research.microsoft.com/en-us/people/sbkang/

Sudipta Sinha (Microsoft Research):

【Motion estimation】Which Way Are You Going? Imitative Decision Learning for Path Forecasting in Dynamic Scenes

Yuke Li (York University)*:

【Motion estimation】Spatio-temporal Video Re-localization by Warp LSTM

Yang Feng (University of Rochester)*:

Lin Ma (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

【Motion estimation】GPSf M: Global Projective SFM Using Algebraic Constraints\\ on Multi-View Fundamental Matrices

Yoni Kasten (Weizmann Institute )*:

Amnon Geifman (Weizmann Institute):

Meirav Galun (Weizmann Institute of Science):

Ronen Basri (Weizmann Institute of Science): http://www.wisdom.weizmann.ac.il/~ronen/

【Motion estimation】Large-Scale, Metric Structure from Motion for Unordered Light Fields

Sotiris Nousias (University College London)*:

Manolis Lourakis (FORTH – Hellas):

Christos Bergeles (Kings College London):

【Motion estimation】Understanding the Limitations of CNN-based Absolute Camera Pose Regression

Torsten Sattler (Chalmers University of Technology)*:

Qunjie Zhou (Technical University of Munich):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

Laura Leal-Taixé (TUM):

【Motion estimation】Segmentation-driven 6D Object Pose Estimation

Yinlin Hu (EPFL)*:

Joachim Hugonot (EPFL):

Pascal Fua (EPFL, Switzerland): http://cvlabwww.epfl.ch/~fua/

Mathieu Salzmann (EPFL):

【Motion estimation】Polarimetric Camera Calibration Using an LCD Monitor

Zhixiang Wang (National Taiwan University):

Yinqiang Zheng (National Institute of Informatics)*: https://researchmap.jp/yinqiangzheng

Yung-Yu Chuang (National Taiwan University):

【Motion estimation】Jumping Manifolds: Geometry Aware Dense Non-Rigid Structure from Motion

Suryansh Kumar (ANU (Australian National University))*:

【Motion estimation】Privacy Preserving Image-based Localization

Pablo Speciale (ETH Zurich)*:

Johannes L Schönberger (Microsoft):

Sing Bing Kang (Microsoft Research): http://research.microsoft.com/en-us/people/sbkang/

Sudipta Sinha (Microsoft Research):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

【Motion estimation】Recurrent Neural Network for

Rui Wang (University of North Carolina at Chapel Hill)*:

Stephen Pizer (University of North Carolina at Chapel Hill):

Jan-Michael Frahm (UNC-Chapel Hill):

【Motion estimation】Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion

Zhenpei Yang (The University of Texas at Austin):

Kristen Grauman (Facebook AI Research & UT Austin): http://www.cs.utexas.edu/~grauman/

Qixing Huang (The University of Texas at Austin)*:

Linjie Luo (Snap Inc):

Xiaowei Zhou (Zhejiang Univ., China):

Jeffrey Pan (Austin, Texas):

【Motion estimation】Structure-And-Motion-Aware Rolling Shutter Correction

Bingbing Zhuang (NUS)*:

Quoc-Huy Tran (NEC Labs America):

Pan Ji (NEC Labs):

Loong Fah Cheong (NUS):

Manmohan Chandraker (NEC Labs America): http://cseweb.ucsd.edu/~mkchandraker/

【Motion estimation】PVNet: Pixel-wise Voting Network for 6Do F Pose Estimation

sida peng (Zhejiang University):

Yuan Liu (Zhejiang University):

Qixing Huang (The University of Texas at Austin):

Hujun Bao (Zhejiang University):

Xiaowei Zhou (Zhejiang Univ., China)*:

【Motion estimation】Lending Orientation to Neural Networks for Cross-view Geo-localization

Liu liu (ANU (Australian National University))*:

HONGDONG LI (Australian National University, Australia):

【Motion estimation】Visual Localization by Learning Objects-of-Interest Dense Match Regression

Philippe Weinzaepfel (Naver Labs Europe)*:

Gabriela Csurka (Naver Labs Europe):

Yohann Cabon (Naver Labs Europe):

Martin Humenberger (Naver Labs Europe):

【Motion estimation】Unsupervised 3D Pose Estimation with Geometric Self-Supervision

Ching-Hang Chen (Amazon Inc.)*:

Ambrish Tyagi (Amazon):

Dylan Drover (Amazon Lab126):

Rohith MV (Amazon Lab126):

James Rehg (Georgia Institute of Technology): http://www.cc.gatech.edu/~rehg/

Stefan Stojanov (Georgia Institute of Technology):

Amit Agrawal (Amazon):

【Motion estimation】Hybrid Scene Compression for Visual Localization

Federico Camposeco (ETH Zurich):

Andrea Cohen (Oculus):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

Torsten Sattler (Chalmers University of Technology)*:

【Motion estimation】The Regretful Agent: Heuristic-Aided Navigation through Progress Estimation

Chih-Yao Ma (Georgia Institute of Technology)*:

Zuxuan Wu (UMD):

Ghassan Al Regib (Georgia Institute of Technology �):

Caiming Xiong (Salesforce Research):

Zsolt Kira (Georgia Institute of Technology):

【Motion estimation】Deep Ch Ar Uco: Dark Ch Ar Uco Marker Pose Estimation

Tomasz Malisiewicz (MIT)*: http://people.csail.mit.edu/tomasz/

Daniel De Tone (Magic Leap):

Danying Hu (Magic Leap):

【Motion estimation】LO-Net: Deep Real-time Lidar Odometry

Qing Li (Xiamen University):

Shaoyang Chen (Xiamen University):

Cheng Wang (Xiamen University)*:

Xin Li (Louisiana State University):

Chenglu Wen (Xiamen University):

Ming Cheng (Xiamen University):

Jonathan Li (Xiamen University):

【Motion estimation】Tra PHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions

Rohan Chandra (University of Maryland)*:

Uttaran Bhattacharya (University of Maryland, College Park):

Aniket Bera (The University of North Carolina at Chapel Hill):

Dinesh Manocha (UMD):

【Motion estimation】What Correspondences Reveal about Unknown Camera and Motion Models?

Thomas Probst (ETH Zurich)*:

Ajad Chhatkuli (ETH Zurich):

Danda Pani Paudel (ETH Zürich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Motion estimation】Learning to Localize through Compressed Binary Maps

Xinkai Wei (Uber ATG, University of Waterloo)*:

Shenlong Wang (Uber ATG, University of Toronto):

Julieta Martinez (Uber ATG):

Ioan Andrei Bârsan (Uber ATG, University of Toronto):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Motion estimation】Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry

Fei Xue (Peking University)*:

Xin Wang (Peking University):

Shunkai Li (Peking University):

Qiuyuan Wang (Peking University):

Junqiu Wang (Beijing Changcheng Aviation Measurement and Control Institute):

Hongbin Zha (Peking University, China): http://www.cis.pku.edu.cn/vision/3DVCR/3DVCR_E.html

【Motion estimation】Deep Mapping: Unsupervised Map Estimation From Multiple Point Clouds

Li Ding (University of Rochester):

Chen Feng (New York University)*:

【Motion estimation】End-to-end Interpretable Neural Motion Planner

Wenyuan Zeng (Uber ATG, University of Toronto):

Wenjie Luo (Uber ATG / University of Toronto)*:

Shun Da Suo (Uber ATG, University of Toronto):

Abbas Sadat (Uber ATG):

Bin Yang (Uber ATG & University of Toronto):

Sergio Casas Romero (Uber ATG, University of Toronto):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Motion estimation】Selective Sensor Fusion for Neural Visual-Inertial Odometry

Changhao Chen (University of Oxford)*:

Stefano Rosa (University of Oxford):

Yishu Miao (University of Oxford):

Chris Xiaoxuan Lu (University of Oxford):

Wei Wu (Tencent):

Andrew Markham (University of Oxford):

Niki Trigoni (University of Oxford):

【Motion estimation】Perturbation Analysis of the 8-Point Algorithm: a Case Study for Wide Fo V Cameras

Thiago L T da Silveira (Federal University of Rio Grande do Sul)*:

Claudio R Jung (UFRGS):

【Motion estimation】The Alignment of the Spheres: Globally-Optimal Spherical Mixture Alignment for Camera Pose Estimation

Dylan Campbell (Australian National University)*:

Lars Petersson (Data61/CSIRO):

Laurent Kneip (Shanghai Tech University):

HONGDONG LI (Australian National University, Australia):

Stephen Gould (Australian National University, Australia): http://users.cecs.anu.edu.au/~sgould/index.html

【Motion estimation】Deep Single Image Camera Calibration with Radial Distortion

Manuel Lopez-Antequera (Mapillary)*:

Roger Marí Molas (CMLA, ENS Cachan):

Pau Gargallo (Mapillary):

Yubin Kuang (Mapillary AB):

Javier Gonzalez-Jimenez (University of Malaga):

Gloria Haro (Universitat Pompeu Fabra):

【Motion estimation】Crowd Pose: Efficient Crowded Scenes Pose Estimation and A New Benchmark

Jiefeng Li (Shanghai Jiao Tong University):

Can Wang (SJTU):

Hao Zhu (Shanghai Jiao Tong University):

Yihuan Mao (Tsinghua Univerisity):

Hao-Shu Fang (SJTU):

Cewu Lu (Shanghai Jiao Tong University)*: http://mvig.sjtu.edu.cn/

【Motion estimation】Dense Pose-Slim: Cheaper Learning from Motion Cues

Natalia Neverova (Facebook AI Research)*:

James Thewlis (University of Oxford):

Alp Guler (Imperial College London):

Iasonas Kokkinos (UCL): http://cvn.ecp.fr/personnel/iasonas/index.html

Andrea Vedaldi (Oxford University): http://www.robots.ox.ac.uk/~vedaldi/index.html

【Motion estimation】An Efficient Schmidt-EKF for 3D Visual-Inertial SLAM

Patrick Geneva (University of Delaware)*:

James Maley (University of Delaware):

Guoquan Huang (University of Delaware):

【Motion estimation】Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation

Haofu Liao (University of Rochester)*:

Wei-An Lin (The University of Maryland, College Park):

Jiarui Zhang (Rutgers University):

Jingdan Zhang (Z2AI Corporation):

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

  1. Kevin Zhou (ICT):

【Motion estimation】From Coarse to Fine: Robust Hierarchical Localization at Large Scale

Paul-Edouard Sarlin (ETH Zürich Autonomous Systems Lab):

Cesar Cadena (ETH Zurich):

Roland Siegwrat (ETH Zürich Autonomous Systems Lab):

Marcin T Dymczyk (Sevensense Robotics AG)*:

【Stereo matching】Finding Task-Relevant Features for Few-Shot Learning by Category Traversal

Hongyang Li (The Chinese University of Hong Kong)*:

David Eigen (Clarifai Inc.):

Samuel Dodge (Clarifai Inc.):

Matt Zeiler (Clarifai Inc.):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【Stereo matching】Driving Stereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios

Guorun Yang (Tsinghua University)*:

Xiao Song (Sensetime Group Limited):

Chaoqin Huang (Shanghai Jiao Tong University):

Zhidong Deng (Tsinghua University):

Jianping Shi (Sensetime Group Limited):

Bolei Zhou (CUHK):

【Stereo matching】GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

Feihu Zhang (University of Oxford)*:

Victor Adrian Prisacariu (University of Oxford):

Yang Ruigang (Baidu):

Philip Torr (University of Oxford): http://www.robots.ox.ac.uk/~tvg/

【Stereo matching】Real-time self-adaptive deep stereo

Alessio Tonioni (University of Bologna):

Fabio Tosi (University of Bologna):

Matteo Poggi (University of Bologna)*:

Stefano Mattoccia (University of Bologna):

Luigi Di Stefano (University of Bologna):

【Stereo matching】LAF-Net: Locally Adaptive Fusion Networks for Stereo Confidence Estimation

Sunok Kim (Yonsei University):

Seungryong Kim (Yonsei University):

Dongbo Min (Ewha Womans University):

Kwanghoon Sohn (Yonsei Univ.)*: http://diml.yonsei.ac.kr/professor.html

【Stereo matching】Guided Stereo Matching

Matteo Poggi (University of Bologna)*:

Davide Pallotti (University of Bologna):

Fabio Tosi (University of Bologna):

Stefano Mattoccia (University of Bologna):

【Stereo matching】Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion

Alex Z Zhu (University of Pennsylvania)*:

Liangzhe Yuan (University of Pennsylvania):

Kenneth Chaney (University of Pennsylvania):

Kostas Daniilidis (University of Pennsylvania):

【Stereo matching】Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence

Hsueh-Ying Lai (National Chiao Tung University):

Yi-Hsuan Tsai (NEC Labs America):

Wei-Chen Chiu (National Chiao Tung University)*:

【Stereo matching】Group-wise Correlation Stereo Network

Xiaoyang Guo (The Chinese University of Hong Kong)*:

Kai Yang (Sense Time Research):

Wukui Yang (Sense Time Research):

Hongsheng Li (Chinese University of Hong Kong):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【Stereo matching】Multi-Level Context Ultra-Aggregation for Stereo Matching

Guang-Yu Nie (Beijing Institute of Technology):

Ming-Ming Cheng (Nankai University):

Yun Liu (Nankai University):

Zhengfa Liang (Southwest Electronics and Telecommunication Technology Research Institute):

Deng-Ping Fan (Nankai University):

Yue Liu (Beijing Institute of Technology)*:

Yongtian Wang (Beijing Institute of Technology):

【Stereo matching】Deep Li DAR: Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse Li DAR Data and Single Color Image

Jiaxiong Qiu (UESTC):

Zhaopeng Cui (ETH Zurich)*:

Yinda Zhang (Princeton University):

xingdi zhang (UESTC):

Shuaicheng Liu (UESTC:

Megvii):

Bing Zeng (University of Electronic Science and Technology of China):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

【Stereo matching】Dense Depth Posterior

Yanchao Yang (UCLA)*:

Alex Wong (University of California, Los Angeles):

Stefano Soatto (UCLA): http://vision.ucla.edu/projects.html

【Stereo matching】Veritatem Dies Aperit – Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach

Amir Atapour-Abarghouei (Durham University)*:

Toby Breckon (Durham University):

【Stereo matching】Towards Scene Understanding: Unsupervised Monocular Depth Estimation with Semantic-aware Representation

Po-Yi Chen (National Taiwan University):

Alexander H. Liu (National Taiwan University):

Yen-Cheng Liu (Georgia Institute of Technology):

Yu-Chiang Frank Wang (National Taiwan University)*: http://www.citi.sinica.edu.tw/pages/ycwang/index_en.html

【Stereo matching】A Bayesian Perspective on the Deep Image Prior

zezhou cheng (university of massachusetts amherst)*:

Matheus A Gadelha (University of Massachusetts Amherst):

Subhransu Maji (University of Massachusetts, Amherst): http://people.cs.umass.edu/~smaji/

Daniel Sheldon (University of Massachusetts, Amherst):

【Stereo matching】Multi-Scale Geometric Consistency Guided Multi-View Stereo

Qingshan Xu (Huazhong University of Science and Technology):

Wenbing Tao (Huazhong University of Science and Technology)*:

【Stereo matching】Hierarchical deep stereo matching on high-resolution images

Gengshan Yang (Carnegie Mellon University)*:

Joshua Manela (Argo AI):

Deva Ramanan (Carnegie Mellon University): http://www.ics.uci.edu/~dramanan/

Michael Happold (Argo AI, LLC):

【Stereo matching】Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference

Yao Yao (The Hong Kong University of Science and Technology):

Zixin Luo (HKUST)*:

Shiwei Li (HKUST):

Tianwei Shen (HKUST):

Tian Fang (HKUST):

Long Quan (Hong Kong University of Science and Technology): http://visgraph.cs.ust.hk/index.html

【Stereo matching】Learning Single-Image Depth from Videos using Quality Assessment Networks

Weifeng Chen (University of Michigan, Ann Arbor)*:

Shengyi Qian (University of Michigan, Ann Arbor):

Jia Deng (Princeton University):

【Stereo matching】Bilateral Cyclic Constraint and Adaptive Regularization for Monocular Depth Prediction

Alex Wong (University of California, Los Angeles)*:

Stefano Soatto (UCLA): http://vision.ucla.edu/projects.html

【Stereo matching】Learning to Minify Photometric Stereo

Junxuan Li (The Australian National University)*:

Shaodi You (Data61-CSIRO):

Yasuyuki Matsushita (Osaka University):

Antonio Robles-Kelly (Deakin University):

【Stereo matching】Depth from a polarisation + RGB stereo pair

DIZHONG ZHU (University of York)*:

William Smith (University of York):

【Stereo matching】Connecting the Dots: Learning Representations for Active Monocular Depth Estimation

Gernot Riegler (Intel Labs)*:

Yiyi Liao (MPI Tuebingen):

Simon Donné (MPI-IS):

Vladlen Koltun (Intel Labs): http://vladlen.info/publications/

Andreas Geiger (MPI-IS and University of Tuebingen):

【Stereo matching】Learning Non-Volumetric Depth Fusion using Successive Reprojections

Simon Donné (MPI-IS and University of Tübingen)*:

Andreas Geiger (MPI-IS and University of Tuebingen):

【Stereo matching】Unsupervised Learning of Depth from Defocus Using a Gaussian PSF Layer

Shir Gur (Tel Aviv University):

Lior Wolf (Tel Aviv University, Israel)*: http://www.cs.tau.ac.il/~wolf/

【Stereo matching】Un OS: Unified Unsupervised Optical-flow and Stereo-depth Estimation by Watching Videos

Yang Wang (Baidu USA)*:

Peng Wang (Baidu USA LLC.):

Zhenheng Yang (Facebook Research):

Chenxu Luo (Johns Hopkins University):

Yi Yang (Baidu Research): http://www.cs.cmu.edu/~yiyang/

Wei Xu (Baidu Research):

【Stereo matching】Self-calibrating Deep Photometric Stereo Networks

Guanying Chen (The University of Hong Kong)*:

Kai Han (University of Oxford):

Boxin Shi (Peking University):

Yasuyuki Matsushita (Osaka University):

Kwan-Yee K. Wong (The University of Hong Kong):

【Stereo matching】Learning to Adapt for Stereo

Alessio Tonioni (University of Bologna)*:

Tom Joy (University of Oxford):

Oscar Rahnama (University of Oxford):

Luigi Di Stefano (University of Bologna):

Thalaiyasingam Ajanthan (University of Oxford):

Philip Torr (University of Oxford): http://www.robots.ox.ac.uk/~tvg/

【Stereo matching】Monocular Depth Estimation Using Relative Depth Maps

Jaehan Lee (Korea University)*:

Chang-Su Kim (Korea university): http://mcl.korea.ac.kr/people/professor/

【Stereo matching】Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation

Andrea Pilzer (Università di Trento)*:

Stéphane Lathuiliere (university of Trento):

Nicu Sebe (University of Trento):

Elisa Ricci (FBK – Technologies of Vision):

【Stereo matching】Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation

Shanshan Zhao (The University of Sydney)*:

Huan Fu (The University of Sydney):

Mingming Gong (University of Pittsburgh):

Dacheng Tao (University of Sydney):

【Stereo matching】Learning monocular depth estimation infusing traditional stereo knowledge

Fabio Tosi (University of Bologna):

Filippo Aleotti (University of Bologna):

Matteo Poggi (University of Bologna)*:

Stefano Mattoccia (University of Bologna):

【Stereo matching】Stereo DRNet: Dilated Residual Stereo Net

Rohan Chabra (University of North Carolina at Chapel Hill)*:

Julian Straub (Facebook Reality Labs):

Christopher Sweeny (Facebook Reality Labs):

Richard Newcombe (“Facebook / Occulus, USA”):

Henry Fuchs (unc):

【Stereo matching】CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth Prediction

José M Fácil (University of Zaragoza)*:

Benjamin Ummenhofer (Intel Labs):

Huizhong Zhou (The University of Freiburg):

Luis Montesano (University of Zaragoza:

Bitbrain):

Thomas Brox (University of Freiburg): http://lmb.informatik.uni-freiburg.de/people/brox/index.en.html

Javier Civera (Universidad de Zaragoza):

【Stereo matching】Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

Anurag Ranjan (MPI for Intelligent Systems)*:

Varun Jampani (Nvidia Research):

Kihwan Kim (NVIDIA):

Deqing Sun (NVIDIA): http://cs.brown.edu/~dqsun/index.html

Lukas Balles (University of Tuebingen):

Jonas Wulff (Massachusetts Institute of Technology):

Michael J. Black (Max Planck Institute for Intelligent Systems): http://ps.is.tue.mpg.de/person/black

【Stereo matching】Depth Coefficients for Depth Completion

Saif M Imran (Michigan State University)*:

Yunfei Long (Michigan State University):

Xiaoming Liu (Michigan State University):

Daniel Morris (MSU):

【Optical flow】Deep Structured Scene Flow

Wei-Chiu Ma (MIT)*:

Shenlong Wang (Uber ATG, University of Toronto):

Rui Hu (Uber):

Yuwen Xiong (Uber ATG:

University of Toronto):

Raquel Urtasun (Uber ATG): http://www.cs.toronto.edu/~urtasun/

【Optical flow】Creative Flow+ Dataset

Maria Shugrina (University of Toronto)*:

Ziheng Liang (University of British Columbia):

Amlan Kar (University of Toronto):

Jiaman Li (University of Toronto):

Angad Singh (Evertz Microsystems):

Karan Singh (University of Toronto):

Sanja Fidler (University of Toronto):

【Optical flow】Learning Optical Flow with Occlusion Hallucination

Pengpeng Liu (The Chinese University of Hong Kong)*:

Michael Lyu (The Chinese University of Hong Kong):

Irwin King (The Chinese University of Hong Kong):

Jia Xu (Tencent AI Lab):

【Optical flow】Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation

Junhwa Hur (TU Darmstadt)*:

Stefan Roth (TU Darmstadt): http://www.igp.ethz.ch/photogrammetry/

【Optical flow】Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes

Yiran Zhong (Australian National University)*:

Pan Ji (NEC Laboratories America):

Yuchao Dai (Northwestern Polytechnical University):

Jianyuan Wang (Australian National University):

HONGDONG LI (Australian National University, Australia):

【Region matching】NM-Net: Mining Reliable Neighbors for Robust Feature Correspondences

Chen Zhao (Huazhong University of Science and Technology):

Zhiguo Cao (Huazhong Univ. of Sci.&Tech.):

chi li (Huazhong University of Science and Technology):

Xin Li (West Virginia University):

Jiaqi Yang (Huazhong Univ. of Sci.&Tech.)*:

【Region matching】SFNet: Learning Object-aware Semantic Correspondence

Junghyup Lee (Yonsei University):

DOHYUNG KIM (YONSEI UNIVERSITY):

Jean Ponce (Inria): http://www.di.ens.fr/willow/

Bumsub Ham (Yonsei University)*:

【Region matching】SDC – Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks

René Schuster (DFKI)*:

Oliver Wasenmüller (DFKI):

Christian Unger (BMW):

Didier Stricker (DFKI): https://av.dfki.de/members/stricker/

【Region matching】Learning Correspondence from the Cycle-consistency of Time

Xiaolong Wang (CMU)*:

Allan Jabri (UC Berkeley):

Alexei A Efros (UC Berkeley):

【Region matching】Networks for Joint Affine and Non-parametric Image Registration

Zhengyang Shen (UNC)*:

Xu Han (UNC Chapel Hill):

Zhenlin Xu (UNC Chapel Hill):

Marc Niethammer (UNC):

【Region matching】Unsupervised Learning of Dense Shape Correspondence

Oshri Halimi (Technion)*:

Or Litany (Facebook AI Research):

Emanuele Rodola (Sapienza University of Rome):

Alex Bronstein (Tel Aviv University, Israel):

Ron Kimmel (Technion):

【Region matching】Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision

Alireza Zaeemzadeh (University of Central Florida)*:

Mohsen Joneidi (University of Central Florida):

Nazanin Rahnavard (University of Central Florida):

Mubarak Shah (University of Central Florida): http://crcv.ucf.edu/people/faculty/shah.html

【Region matching】GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching

Simone Melzi (University of Verona)*:

Riccardo Spezialetti (Universita’ degli studi di Bologna):

Federico Tombari (Technical University of Munich, Germany): http://vision.deis.unibo.it/fede/

Michael Bronstein (Università della Svizzera Italiana):

Luigi Di Stefano (University of Bologna):

Emanuele Rodola (Sapienza University of Rome):

【Region matching】RF-Net: An End-to-End Image Matching Network based on Receptive Field

Xuelun Shen (Xiamen University):

Cheng Wang (Xiamen University)*:

Zenglei Yu (XIamen University):

Xin Li (Louisiana State University):

Jonathan Li (Xiamen University):

Chenglu Wen (Xiamen University):

Ming Cheng (Xiamen University):

Zijian He (Xiamen University):

【Region matching】Unsupervised Image Matching and Object Discovery as Optimization

Huy V. Vo (Ecole Normale Supérieure – INRIA – Valeo.ai)*:

Jean Ponce (Inria): http://www.di.ens.fr/willow/

Patrick Pérez (Valeo.ai):

Francis Bach (INRIA – Ecole Normale Supérieure):

Yann Le Cun (New York University): http://yann.lecun.com/

Minsu Cho (POSTECH):

Kai Han (University of Oxford):

【Region matching】Metric Learning for Image Registration

Marc Niethammer (UNC)*:

Roland Kwitt (“University of Salzburg, Austria”):

Francois-Xavier Vialard (University Paris-Est):

【Region matching】QATM: Quality-Aware Template Matching For Deep Learning

Jiaxin Cheng (USC Information Sciences Institute)*:

Yue Wu (USC ISI):

Wael Abd-Almageed (Information Sciences Institute):

Prem Natarajan (USC ISI):

【Region matching】Boosting Local Shape Matching for Dense 3D Face Correspondence

Zhenfeng Fan (The Chinese academy of science)*:

hu xiyuan (The Chinese academy of science):

Chen Chen (The Chinese academy of science):

peng silong (The Chinese academy of science):

【Region matching】Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope

Tolga Birdal (TU Munich)*:

Umut Simsekli (Telecom Paris Tech):

【Region matching】A convex relaxation for multi-graph matching

Paul Swoboda (MPI fuer Informatik, Saarbruecken)*:

Ashkan Mokarian (BIH/MDC):

Dagmar Kainmueller (BIH/MDC):

Christian Theobalt (MPI Informatik):

Florian Bernard (Max Planck Institute for Informatics):

【Image editing】Zoom in with Meta-SR: A Magnification-Arbitrary Network for Super-Resolution

Xuecai Hu (USTC)*:

Haoyuan Mu (Tsinghua University):

Xiangyu Zhang (Megvii Inc):

Zilei Wang (University of Science and Technology of China):

Jian Sun (Megvii Technology): http://research.microsoft.com/en-us/groups/vc/

Tieniu Tan (NLPR, China): http://lab.datatang.com/1984DA173065/Default.aspx

【Image editing】Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net

Qi Xie (Xi’an Jiaotong University)*:

Minghao Zhou (Xi’an Jiaotong University):

Deyu Meng (Xi’an Jiaotong University):

Qian Zhao (Xi’an Jiaotong University ):

Wangmeng Zuo (Harbin Institute of Technology, China):

Zongben Xu (Xi’an Jiaotong University):

【Image editing】Blind Super-Resolution With Iterative Kernel Correction

Jinjin Gu (The Chinese University of Hong Kong, Shenzhen)*:

Hannan Lu (Harbin Institute of Technology):

Wangmeng Zuo (Harbin Institute of Technology, China):

Chao Dong (SIAT):

【Image editing】Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning

Ruoteng Li (National University of Singapore)*:

Loong Fah Cheong (NUS):

Robby Tan (“Yale-NUS College, Singapore”):

【Image editing】Learning to Calibrate Straight Lines for Fisheye Image Rectification

Zhucun Xue (Wu Han university):

Nan Xue (Wuhan University):

Gui-Song Xia (Wuhan University)*:

Weiming Shen (Wuhan University):

【Image editing】Camera Lens Super-Resolution

Chang Chen (University of Science and Technology of China):

Zhiwei Xiong (University of Science and Technology of China)*:

Xinmei Tian (USTC):

Zheng-Jun Zha (University of Science and Technology of China):

Feng Wu (University of Science and Technology of China):

【Image editing】Spatially Variant Linear Representation Models for Joint Filtering

Jinshan Pan (Nanjing University of Science and Technology)*:

Jiangxin Dong (Dalian University of Technology):

Jimmy Ren (Sense Time Research):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

Jinhui Tang (Nanjing University of Science and Technology):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Image editing】Toward Convolutional Blind Denoising of Real-world Noisy Photographs

Shi Guo (Harbin Institute of Technology):

Zifei Yan (Harbin Institute of Technology):

Kai Zhang (Harbin Institute of Technology):

Wangmeng Zuo (Harbin Institute of Technology, China)*:

Lei Zhang (“Hong Kong Polytechnic University, Hong Kong, China”): http://www4.comp.polyu.edu.hk/~cslzhang/

【Image editing】Towards Real Scene Super-Resolution with Raw Images

Xiangyu Xu (Tsinghua University)*:

Yongrui Ma (sensetime):

Wenxiu Sun (Sense Time Research):

【Image editing】ODE-inspired Network Design for Single Image Super-Resolution

Xiangyu He (Institute of Automation, Chinese Academy of Sciences)*:

Zitao Mo (Chinese Academy of Sciences):

Peisong Wang (Institute of Automation, Chinese Academy of Sciences):

Yang Liu (Alibaba Group):

Mingyuan Yang (Alibaba):

Jian Cheng (“Chinese Academy of Sciences, China”): http://www.nlpr.ia.ac.cn/jcheng/

【Image editing】Blind Image Deblurring With Local Maximum Gradient Prior

Liang Chen (East China Normal University):

Faming Fang (East China Normal University)*:

Tingting Wang (East China Normal University):

Guixu Zhang (East China Normal University):

【Image editing】Attention-guided Network for Ghost-free High Dynamic Range Imaging

Qingsen Yan (Northwestern Polytechnical University):

Dong Gong (The University of Adelaide)*:

Qinfeng Shi (University of Adelaide): https://cs.adelaide.edu.au/~javen/

Anton van den Hengel (University of Adelaide):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

Yanning Zhang (Northwestern Polytechnical University):

【Image editing】Semantic Image Synthesis with Spatially-Adaptive Normalization

Taesung Park (UC Berkeley)*:

Ming-Yu Liu (NVIDIA):

Ting-Chun Wang (NVIDIA):

Jun-Yan Zhu (MIT):

【Image editing】Zoom to Learn, Learn to Zoom

Xuaner Zhang (UC Berkeley)*:

Qifeng Chen (HKUST):

Ren Ng (UC Berkeley):

Vladlen Koltun (Intel Labs): http://vladlen.info/publications/

【Image editing】Single Image Deraining: A Comprehensive Benchmark Analysis

siyuan li (Tianjin university)*:

Iago Breno A. do C. Araujo (USP):

Wenqi Ren (Institute of Information Engineering, Chinese Academy of Sciences):

Zhangyang Wang (TAMU):

Eric K. Tokuda (Usp):

Roberto Hirata Junior (USP):

Roberto Cesar-Junior (Usp):

Jiawan Zhang (Tianjin University):

Xiaojie Guo (Tianjin University):

Xiaochun Cao (Chinese Academy of Sciences):

【Image editing】Dynamic Scene Deblurring with Parameter Selective Sharing and Nested Skip Connections

Hongyun Gao (The Chinese University of Hong Kong)*:

Xin Tao (Tencent):

Xiaoyong Shen (Tencent):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Image editing】Feedback Network for Image Super-Resolution

Zhen Li (Sichuan University):

Jinglei Yang (University of California, Santa Barbara):

Zheng Liu (University of British Columbia):

Xiaomin Yang (Sichuan University)*:

Gwanggil Jeon (Incheon National University ):

Wei Wu (Sichuan University):

【Image editing】Progressive Image Deraining Networks: Simpler and Better

Dongwei Ren (Tianjin University)*:

Wangmeng Zuo (Harbin Institute of Technology, China):

Qinghua Hu (Tianjin University):

Pengfei Zhu (tianjin university):

Deyu Meng (Xi’an Jiaotong University):

【Image editing】Blind Geometric Distortion Correction on Images Through Deep Learning

Xiaoyu LI (Hong Kong University of Science and Technology)*:

Bo Zhang (Hong Kong University of Science and Technology):

Pedro Sander (HKUST):

Jing Liao (City University of Hong Kong):

【Image editing】Reliable and Efficient Image Cropping: A Grid Anchor based Approach

hui zeng (The Hong Kong Polytechnic University)*:

lida li (The Hong Kong Polytechnic University):

zisheng cao (Da-Jiang Innovations):

Lei Zhang (“Hong Kong Polytechnic University, Hong Kong, China”): http://www4.comp.polyu.edu.hk/~cslzhang/

【Image editing】Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring

Hongguang Zhang (Australian National University)*:

Yuchao Dai (Northwestern Polytechnical University):

HONGDONG LI (Australian National University, Australia):

Piotr Koniusz (Data61/CSIRO, ANU):

【Image editing】Phase-only Image Based Kernel Estimation for Single-image Blind Deblurring

Liyuan Pan (The Australian National University)*:

Miaomiao Liu (The Australian National University):

Yuchao Dai (Northwestern Polytechnical University):

RICHARD HARTLEY (Australian National University, Australia):

【Image editing】FOCNet: A Fractional Optimal Control Network for Image Denoising

Xixi Jia (Xidian University)*:

Sanyang Liu ( Xidian University):

Xiangchu Feng ( Xidian University):

Lei Zhang (“Hong Kong Polytechnic University, Hong Kong, China”): http://www4.comp.polyu.edu.hk/~cslzhang/

【Image editing】Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration

Xing Liu (Tohoku university)*:

Masanori Suganuma (RIKEN AIP / Tohoku University):

Zhun Sun (RIKEN Center for AIP):

Takayuki Okatani (Tohoku University/RIKEN AIP):

【Image editing】Probabilistic End-to-end Noise Correction for Learning with Noisy Labels

Kun Yi (Nanjing University):

Jianxin Wu (Nanjing University)*:

【Image editing】Image Super-Resolution by Neural Texture Transfer

Zhifei Zhang (University of Tennessee)*:

Zhaowen Wang (Adobe Research):

Zhe Lin (Adobe Research): http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Hairong Qi (University of Tennessee-Knoxville):

【Image editing】Conditional Adversarial Generative Flow for Controllable Image Synthesis

Rui Liu (Chinese University of Hong Kong)*:

Yu Liu (The Chinese University of Hong Kong):

Xinyu Gong (Texas A&M University ):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Hongsheng Li (Chinese University of Hong Kong):

【Image editing】Blind Visual Motif Removal from a Single Image

Amir Hertz (Tel Aviv University)*:

Sharon Fogel (Tel-Aviv university):

Rana Hanocka (TAU):

Raja Giryes (Tel Aviv University):

Danny Cohen-Or (Tel Aviv University):

【Image editing】Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising

Wei He (RIKEN AIP)*:

Quanming Yao (4Paradigm):

Chao Li (RIKEN):

Naoto Yokoya (RIKEN Center for Advanced Intelligence Project (AIP)):

Qibin Zhao (RIKEN):

【Image editing】Deep Exemplar-based Video Colorization

Bo Zhang (Hong Kong University of Science and Technology)*:

Mingming He (Hong Kong University of Science and Technology):

Jing Liao (City University of Hong Kong):

Pedro Sander (HKUST):

Lu Yuan (Microsoft): http://research.microsoft.com/en-us/um/people/luyuan/index.htm

Amine Bermak (Hong Kong University of Science and Technology):

Dong Chen (Microsoft Research Asia):

【Image editing】Recurrent Neural Networks with Intra-Frame Iterations for Video Deblurring

Seungjun Nah (Seoul National University):

Sanghyun Son (Seoul National University):

Kyoung Mu Lee (Seoul National University)*: http://cv.snu.ac.kr/kmlee/

【Image editing】Learning to Extract Flawless Slow Motion from Blurry Videos

Meiguang Jin (University of Bern)*:

Zhe Hu (Hikvision Research):

Paolo Favaro (University of Bern):

【Image editing】Text2Scene: Generating Compositional Scenes from Textual Descriptions

Fuwen Tan (University of Virginia)*:

Song Feng (IBM Research):

Vicente Ordonez (University of Virginia):

【Image editing】Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining

Rajeev Yasarla ( Johns Hopkins University, Whiting School of Engineering)*:

Vishal Patel (Johns Hopkins University):

【Image editing】Toward Realistic Image Composition with Adversarial Training

Bor-Chun Chen (University of Maryland)*:

Andrew Kae (Oath):

【Image editing】A Flexible Convolutional Solver for Fast Style Transfers

Gilles Puy (Technicolor)*:

Patrick Pérez (Valeo.ai):

【Image editing】Tra Ve LGAN: Image-to-image Translation by Transformation Vector Learning

Matthew Amodio (Yale University)*:

Smita Krishnaswamy ():

【Image editing】Attention-based Adaptive Selection of Operations for Image Restoration in the Presence of Unknown Combined Distortions

Masanori Suganuma (RIKEN AIP / Tohoku University)*:

Xing Liu (Tohoku university):

Takayuki Okatani (Tohoku University/RIKEN AIP):

【Image editing】Sphere PHD: Applying CNNs on a Spherical Poly He Dron Representation of 360◦ Images

Kuk-Jin Yoon (KAIST)*: https://cvl.gist.ac.kr/introduction.html

Yeonkun Lee (KAIST):

Jaeseok Jeong (KAIST):

Jongseob Yun (KAIST):

Wonjune Cho (KAIST):

【Image editing】Disentangling Latent Hands for Image Synthesis and Pose Estimation

Linlin Yang ( University of Bonn):

Angela Yao (National University of Singapore)*:

【Image editing】Using a Transformation Content Block For Image Style Transfer

Dmytro Kotovenko (Heidelberg University)*:

Artsiom O Sanakoyeu (Heidelberg University):

Bjorn Ommer (Heidelberg University):

Sabine Lang (Heidelberg University):

Pingchuan Ma (Heidelberg University):

【Image editing】Style Transfer by Relaxed Optimal Transport and Self-Similarity

Nicholas I Kolkin (Toyota Technological Institute at Chicago)*:

Jason Salavon (University of Chicago):

Greg Shakhnarovich (TTI-Chicago):

【Image editing】A variational EM framework with adaptive edge selection for blind motion deblurring

Liuge Yang (National University of Singapore):

Hui Ji (National University of Singapore)*:

【Image editing】Unsupervised Domain-Specific Deblurring via Disentangled Representations

Boyu Lu (University of Maryland)*:

Jun-Cheng Chen (University of Maryland):

Rama Chellappa (University of Maryland):

【Image editing】Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution

Raied RA Aljadaany (CMU)*:

Dipan K Pal (Carnegie Mellon University):

Marios Savvides (Carnegie Mellon University):

【Image editing】Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior

Magauiya Zhussip (UNIST):

Shakarim Soltanayev (UNIST):

Se Young Chun (Ulsan National Institute of Science and Technology)*:

【Image editing】A Variational Pan-Sharpening with Local Gradient Constraints

Xinghao Ding (Xiamen University):

Zihuang Lin (xiamen university):

Xueyang Fu (Xiamen University):

Yue Huang (Xiamen University)*:

【Image editing】Content Authentication for Neural Imaging Pipelines: End-to-end Optimization of Photo Provenance in Complex Distribution Channels

Pawel Korus (New York University)*:

Nasir Memon (New York University):

【Image editing】Du Do Net: Dual Domain Network for CT Metal Artifact Reduction

Wei-An Lin (The University of Maryland, College Park)*:

Haofu Liao (University of Rochester):

Cheng Peng (The University of Maryland, College Park):

Xiaohang Sun (Princeton University):

Jingdan Zhang (Z2AI Corporation):

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

Rama Chellappa (University of Maryland):

  1. Kevin Zhou (ICT):

【Image editing】Fast Spatio-Temporal Residual Network for Video Super-Resolution

Sheng Li (School of Computer Science, Wuhan University):

Fengxiang He (The University of Sydney):

Bo Du (School of Compuer Science, Wuhan University)*:

Lefei Zhang (Wuhan University):

Yonghao Xu (Wuhan University):

Dacheng Tao (University of Sydney):

【Image editing】Image-to-Image Translation via Group-wise Deep Whitening and Coloring

Wonwoong Cho (Korea University):

Sungha Choi (Korea University):

David Park (Korea University):

Inkyu Shin (Hanyang University):

Jaegul Choo (Korea University)*: http://davian.korea.ac.kr/

【Image editing】Fast Image Inpainting with Parallel Decoding Network

Min-Cheol Sagong (Korea Univ.):

Yong-Goo Shin (Korea Univiersity):

Seung-Wook Kim (Korea University):

Seung Park (Korea University):

Sung-Jea Ko (Korea University)*:

【Image editing】Model-blind Video Denoising Via Frame-to-frame Training

Thibaud Ehret (CMLA, ENS Cachan)*:

Axel Davy (ENS Paris-Saclay):

Gabriele Facciolo (ENS Paris-Saclay):

Jean-Michel Morel (ENS Paris-Saclay):

Pablo Arias (Université Paris-Saclay):

【Image editing】Hyperspectral Image Super-Resolution with Optimized RGB Guidance

Ying Fu (Beijing Institute of Technology)*:

Tao Zhang (Beijing Institute of Technology):

Yinqiang Zheng (National Institute of Informatics): https://researchmap.jp/yinqiangzheng

Debing Zhang (Deep Glint):

Hua Huang (Beijing Institute of Technology):

【Image editing】A Poisson-Gaussian Denoising Dataset for Real Fluorescence Microscopy Images

Yide Zhang (University of Notre Dame)*:

Yinhao Zhu (University of Notre Dame):

Evan Nichols (University of Notre Dame):

Qingfei Wang (University of Notre Dame):

Siyuan Zhang (University of Notre Dame):

Cody Smith (University of Notre Dame):

Scott Howard (University of Notre Dame):

【Image editing】Coordinate-based Texture Inpainting for Pose-Guided Image Generation

Artur Grigorev (Samsung):

Artem Sevastopolsky (Samsung):

Alexander Vakhitov (Samsung AI Research Center):

Victor Lempitsky (Samsung)*:

【Image editing】Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture

Ning Yu (Max Planck Institute for Informatics)*:

Connelly Barnes (University of Virginia):

Eli Shechtman (Adobe Research, US): http://www.adobe.com/technology/people/seattle/eli-shechtman.html

Mike Lukac (Adobe Research):

Sohrab Amirghodsi (Adobe Research):

【Image editing】Using Unknown Occluders to Recover Hidden Scenes

Adam B Yedidia (Massachusetts Institute of Technology)*:

Manel Baradad Jurjo (MIT):

Christos Thrampoulidis (Massachusetts Institute of Technology):

Bill Freeman (MIT): https://billf.mit.edu/

Gregory W Wornell (MIT):

【Image editing】DAVANet: Stereo Deblurring with View Aggregation

Shangchen Zhou (Sensetime Research)*:

Jiawei Zhang (Sensetime Research):

Jimmy Ren (Sense Time Research):

Wangmeng Zuo (Harbin Institute of Technology, China):

Haozhe Xie (Harbin Institute of Technology):

Jinshan Pan (Nanjing University of Science and Technology):

【Image editing】Unprocessing Images for Learned Raw Denoising

Tim Brooks (Google)*:

Ben Mildenhall (UC Berkeley):

Tianfan Xue (MIT):

Jiawen Chen (Google):

Dillon Sharlet (Google):

Jonathan T Barron (Google Research):

【Image editing】Residual Networks for Light Field Image Super-Resolution

Shuo Zhang (Beijing Jiaotong University)*:

Youfang Lin (Beijing Jiaotong University):

Hao Sheng (Beihang University):

【Image editing】Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers

Jingwen He (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences):

Chao Dong (SIAT)*:

Yu Qiao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences): http://mmlab.siat.ac.cn/yuqiao/

【Image editing】Second-order Attention Network for Single Image Super-resolution

Tao Dai (Tsinghua University)*:

Jianrui Cai (The Hong Kong Polytechnic University, Hong Kong, China):

yongbing zhang (Tsinghua University):

Shutao Xia (Tsinghua University):

Lei Zhang (“Hong Kong Polytechnic University, Hong Kong, China”): http://www4.comp.polyu.edu.hk/~cslzhang/

【Image editing】Learning Parallax Attention for Stereo Image Super-Resolution

Longguang Wang (National University of Defense Technology):

Yingqian Wang (National University of Defense Technology ):

Zhengfa Liang (Southwest Electronics and Telecommunication Technology Research Institute):

Zaiping Lin (National University of Defense Technology):

Jungang Yang (National University of Defense Technology):

Wei An (National University of Defense Technology):

Yulan Guo (National University of Defense Technology)*:

【Image editing】Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset

Tianyu Wang (Dalian University of Technology:

City University of Hong Kong):

Xin Yang (Dalian University of Technology):

Ke Xu (Dalian University of Technology:

City University of Hong Kong):

Shaozhe Chen (Dalian University of Technology):

qiang zhang (Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education. Dalian University.):

Rynson W.H. Lau (City University of Hong Kong)*:

【Image editing】Scalable Convolutional Neural Network for Image Compressed Sensing

Wuzhen Shi (Harbin Institute of Technology)*:

Feng Jiang (Harbin Institute of Technology, Harbin):

Shaohui Liu (Harbin Institute of Technology):

Debin Zhao (Harbin Institute of Technology):

【Computational photography】Detecting Private Information and Its Purpose in Pictures Taken by Blind People

Danna Gurari (University of Texas at Austin):

Qing Li (University of California, Los Angeles):

Chi Lin (University of Texas at Austin):

Yinan Zhao (University of Texas at Austin)*:

Anhong Guo (Carnegie Mellon University):

Abigale Stangl (University of Colorado Boulder):

Jeffrey Bigham (Carnegie Mellon University):

【Computational photography】End-to-End Time-lapse Video Synthesis from a Single Outdoor Image

Seonghyeon Nam (Yonsei University):

Chongyang Ma (Kwai Inc.):

Menglei Chai (Snap Inc.):

William Brendel (Snap Inc.):

Ning Xu (Snap):

Seon Joo Kim (Yonsei Univ.)*:

【Computational photography】Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis

Qi Mao (Peking University)*:

Hsin-Ying Lee (University of California, Merced):

Hung-Yu Tseng (University of California, Merced):

Siwei Ma (Peking University, China):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Computational photography】Pluralistic Image Completion

Chuanxia Zheng (Nanyang Technological University)*:

Tat-Jen Cham (Nanyang Technological University):

Jianfei Cai (Nanyang Technological University): http://www3.ntu.edu.sg/home/asjfcai/

【Computational photography】Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation

Yazeed Alharbi (KAUST)*:

Neil Smith (King Abdullah University of Science and Technology (KAUST)):

Peter Wonka (KAUST):

【Computational photography】Attention-aware Multi-stroke Style Transfer

Yuan Yao (Tsinghua University)*:

Jianqiang Ren (Alibaba):

Xuansong Xie (Alibaba):

Weidong Liu (Tsinghua University):

Yong-Jin Liu (Tsinghua University):

Jun Wang (UCL):

【Computational photography】Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting

Yanhong Zeng (Sun Yat-sen University)*:

Jianlong Fu (Microsoft Research):

Hongyang Chao (Sun Yat-sen University):

Baining Guo (MSR Asia):

【Computational photography】Example-Guided Image Synthesis using Adversarial Networks with Genre Consistency

Miao Wang (Beihang University)*:

Guo-Ye Yang (Tsinghua University):

Ruilong Li (Tsinghua University):

Run-Ze Liang (Tsinghua University):

Song-Hai Zhang (Tsinghua University):

Peter Hall (University of Bath):

Shimin Hu (Tsinghua University): http://cg.cs.tsinghua.edu.cn/prof_hu.htm

【Computational photography】Light Field Messaging with Deep Photographic Steganography

Eric Wengrowski (Rutgers University)*:

Kristin Dana (Rutgers University):

【Computational photography】Im2Pencil: Controllable Pencil Illustration from Photographs

Yijun Li (University of California, Merced)*:

Chen Fang (Byte Dance):

Aaron Hertzmann (Adobe Research):

Eli Shechtman (Adobe Research, US): http://www.adobe.com/technology/people/seattle/eli-shechtman.html

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Computational photography】When Color Constancy Goes Wrong: Correcting Improperly White-Balanced Images

Mahmoud Afifi (York University)*:

Brian Price (Adobe):

Scott Cohen (Adobe Research):

Michael S Brown (York University):

【Computational photography】Beyond Volumetric Albedo — A Surface Optimization Framework for Non-Line-of-Sight Imaging

Chia-Yin Tsai (Carnegie Mellon Unversity)*:

Aswin Sankaranarayanan (Carnegie Mellon University):

Ioannis Gkioulekas (Carnegie Mellon University):

【Computational photography】Reflection Removal Using A Dual-Pixel Sensor

Abhijith Punnappurath (York University)*:

Michael S Brown (York University):

【Computational photography】Practical Coding Function Design for Time of Flight Imaging

Felipe Gutierrez-Barragan (University of Wisconsin-Madison)*:

Syed Azer Reza (University of Wisconsin-Madison):

Andreas Velten (University of Wisconsin – Madison):

Mohit Gupta (“University of Wisconsin-Madison, USA “): http://wisionlab.cs.wisc.edu/people/mohit-gupta/

【Computational photography】Video Magnification in the Wild: Using Fractional Anisotropy in Temporal Distribution

Shoichiro Takeda (NTT Corporation)*:

Yasunori Akagi (NTT Service Evolution Laboratories, NTT Corporation):

Kazuki Okami (NTT Corporation):

Megumi Isogai (NTT Media Intelligence Laboratories):

Hideaki Kimata (NTT):

【Computational photography】Frame-Consistent Recurrent Video Deraining with Dual-Level Flow

Wenhan Yang (City University of Hong Kong)*:

Jiaying Liu (Peking University):

Jiashi Feng (NUS): https://sites.google.com/site/jshfeng/

【Computational photography】Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels

Kai Zhang (Harbin Institute of Technology):

Wangmeng Zuo (Harbin Institute of Technology, China)*:

Lei Zhang (“Hong Kong Polytechnic University, Hong Kong, China”): http://www4.comp.polyu.edu.hk/~cslzhang/

【Computational photography】Sea-thru: A Method to Remove Water From Underwater Images

Derya Akkaynak (Dr.)*:

Tali Treibitz (University of Haifa):

【Computational photography】Deep Network Interpolation for Continuous Imagery Effect Transition

Xintao Wang (The Chinese University of Hong Kong)*:

Ke Yu (The Chinese University of Hong Kong):

Chao Dong (SIAT):

Xiaoou Tang (The Chinese University of Hong Kong): http://mmlab.ie.cuhk.edu.hk/

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

【Computational photography】Noise2Void – Learning Denoising from Single Noisy Images

Alexander Krull (CSBD/MPI-CBG)*:

Tim-Oliver Buchholz (CSBD/MPI-CBG):

Florian Jug (CSBD/MPI-CBG):

【Computational photography】De Fusion NET: Defocus Blur Detection via Recurrently Fusing and Refining Multi-scale Deep Features

Chang Tang (China University of Geosciences)*:

Lizhe Wang (China University of Geosciences):

Albert Zomaya (The University of Sydney):

Xinwang Liu (National University of Defense Technology):

Xinzhong Zhu (Zhejiang Normal University):

【Computational photography】Few-Shot Learning via Saliency-guided Hallucination of Samples

Hongguang Zhang (Australian National University)*:

Jing Zhang (Australian National University):

Piotr Koniusz (Data61/CSIRO, ANU):

【Computational photography】Inverse Render Net: Learning single image inverse rendering

Ye Yu (University of York)*:

William Smith (University of York):

【Computational photography】Shapes and Context: In-the-wild Image Synthesis & Manipulation

Aayush Bansal (Carnegie Mellon University)*:

Yaser Sheikh (CMU): http://www.cs.cmu.edu/~yaser/

Deva Ramanan (Carnegie Mellon University): http://www.ics.uci.edu/~dramanan/

【Computational photography】Progressive Pose Attention Transfer for Person Image Generation

Zhen Zhu (Huazhong University of Science and Technology)*:

Tengteng Huang (Huazhong University of Science and Technology):

Baoguang Shi (Microsoft):

Miao Yu (Huazhong University of Science and Technology):

Bofei Wang (ZTE Corporation):

Xiang Bai (Huazhong University of Science and Technology): http://cloud.eic.hust.edu.cn:8071/~xbai/

【Computational photography】Unsupervised Person Image Generation with Semantic Parsing Transformation

Sijie Song (Peking University)*:

Wei Zhang (JD AI Research):

Jiaying Liu (Peking University):

Tao Mei (AI Research of JD.com):

【Computational photography】Deep View: View synthesis with learned gradient descent

John P Flynn (Google Inc)*:

Michael Broxton (Google):

Paul E Debevec (Google VR):

Graham Fyffe (Google Inc.):

Ryan S. Overbeck (Google Inc.):

Noah Snavely (Google): http://www.cs.cornell.edu/~snavely/

Richard Tucker (Google):

Matthew Du Vall (Google):

【Computational photography】Animating Arbitrary Objects via Deep Motion Transfer

Aliaksandr Siarohin (University of Trento)*:

Stéphane Lathuiliere (university of Trento):

Sergey Tulyakov (Snap Inc):

Elisa Ricci (FBK – Technologies of Vision):

Nicu Sebe (University of Trento):

【Computational photography】Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation

Yingcong Chen (Chinese University of Hong Kong)*:

Xiaogang XU (The Chinese University of Hong Kong):

Zhuotao Tian (Chinese University of Hong Kong):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Computational photography】Inverse Path Tracing for Joint Material and Lighting Estimation

Dejan Azinovic (Technical University of Munich)*:

Tzu-Mao Li (MIT CSAIL):

Matthias Niessner (Technical University of Munich): http://niessnerlab.org/publications.html

Anton Kaplanyan (Facebook Reality Labs):

【Computational photography】Towards Instance-level Image-to-Image Translation

Zhiqiang Shen (UIUC)*:

Jianping Shi (Sensetime Group Limited):

Mingyang Huang (Sensetime Group Limited):

Xiangyang Xue (Fudan University):

Thomas Huang (UIUC):

【Computational photography】Deep Flow Guided Video Inpainting

Rui Xu (CUHK)*:

Xiaoxiao Li (The Chinese University of Hong Kong):

Bolei Zhou (CUHK):

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

【Computational photography】Video Generation from Single Semantic Label Map

Junting Pan (Sensetime):

Chengyu Wang (Sense Time Research):

Xu Jia (Huawei Noah’s Ark Lab):

Jing Shao (Sensetime):

Lu Sheng (The Chinese University of Hong Kong)*:

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【Computational photography】Fully Automatic Video Colorization with Self Regularization and Diversity

Qifeng Chen (HKUST)*:

Chenyang Lei (HKUST):

【Computational photography】Single Image Reflection Removal Beyond Linearity

Qiang Wen (South China University of Technology):

Yinjie Tan (South China University of Technology):

Jing Qin (The Hong Kong Polytechnic University):

Wenxi Liu (Fuzhou University):

Guoqiang Han (South China University of Technology):

Shengfeng He (South China University of Technology)*:

【Computational photography】Learning to Separate Multiple Illuminants in a Single Image

Zhuo Hui (Carnegie Mellon University)*:

Ayan Chakrabarti (Washington University in St. Louis):

Kalyan Sunkavalli (Adobe Research): http://www.eecs.harvard.edu/~kalyans/

Aswin Sankaranarayanan (Carnegie Mellon University):

【Computational photography】Learning Linear Transformations for Fast Image and Video Style Transfer

Xueting Li (University of California, Merced)*:

Sifei Liu (NVIDIA):

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

【Computational photography】Events-to-Video: Bringing Modern Computer Vision to Event Cameras

Henri Rebecq (University of Zurich & ETH Zurich)*:

Rene Ranftl (Intel Labs):

Vladlen Koltun (Intel Labs): http://vladlen.info/publications/

Davide Scaramuzza (University of Zurich & ETH Zurich, Switzerland): http://rpg.ifi.uzh.ch/people_scaramuzza.html

【Computational photography】Recurrent Back-Projection Network for Video Super-resolution

Muhammad Haris (TTI-J)*:

Greg Shakhnarovich (TTI-Chicago):

Norimichi Ukita (TTI-J):

【Computational photography】Predicting visible image differences under varying display brightness and viewing distance

Nanyang Ye (University of Cambridge)*:

Krzysztof Wolski (Max Planck Institut für Informatik):

Rafal Mantiuk (University of Cambridge):

【Computational photography】Causes and Corrections for Bimodal Multipath Scanning with Structured Light

yu zhang (Nanjing University )*:

Daniel Lau (University of Kentucky):

Ying Yu (University of Kentucky):

【Computational photography】Diverse Generation for Multi-agent Sports Games

Raymond A Yeh (UIUC)*:

Alexander Schwing (UIUC): http://www.alexander-schwing.de/

Jonathan Huang (Google): https://ai.google/research/people/JonathanHuang

Kevin Murphy (Google):

【Computational photography】Deep Tree Learning for Zero-shot Face Anti-Spoofing

Yaojie Liu (Michigan State University)*:

Joel Stehouwer (Michigan State University):

Amin Jourabloo (Michigan State University):

Xiaoming Liu (Michigan State University):

【Computational photography】Deep Video Inpainting

Dahun Kim (KAIST)*:

Sanghyun Woo (KAIST):

Joon-Young Lee (Adobe Research):

In So Kweon (KAIST): http://rcv.kaist.ac.kr/

【Computational photography】Foreground-aware Image Inpainting

Wei Xiong (University of Rochester)*:

Jiahui Yu (UIUC):

Zhe Lin (Adobe Research): http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Jimei Yang (Adobe): https://eng.ucmerced.edu/people/jyang44

Xin Lu (Adobe):

Connelly Barnes (University of Virginia):

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

【Computational photography】Art2Real: Unfolding the Reality of Artworks via Semantically-Aware Image-to-Image Translation

Matteo Tomei (University of Modena and Reggio Emilia):

Marcella Cornia (University of Modena and Reggio Emilia):

Lorenzo Baraldi (University of Modena and Reggio Emilia)*:

Rita Cucchiara (Universita Di Modena E Reggio Emilia): http://aimagelab.ing.unimore.it/imagelab/person.asp?idpersona=1

【Computational photography】Structure-Preserving Stereoscopic View Synthesis with Multi-Scale Adversarial Correlation Matching

Yu Zhang (Sense Time Research)*: http://www.comp.hkbu.edu.hk/~yuzhang/

Dongqing Zou (Sense Time Research):

Jimmy Ren (Sense Time Research):

Zhe Jiang (Sense Time Research):

Xiaohao Chen (Sense Time Research):

【Computational photography】Dyn Typo: Example-based Dynamic Text Effects Transfer

Yifang Men (Peking University)*:

Zhouhui Lian (Peking University):

Jianguo Xiao (PKU):

Yingmin Tang (PKU):

【Computational photography】Arbitrary Style Transfer with Style-Attentional Networks

Dae Young Park (AIRI):

Kwang Hee Lee (Boeing Korea Engineering and Technology Center (BKETC))*:

【Computational photography】Typography with Decor: Intelligent Text Style Transfer

Wenjing Wang (Peking University)*:

Jiaying Liu (Peking University):

Shuai Yang ( Peking University):

Zongming Guo (Peking University):

【Computational photography】Photo Wake-Up: 3D Character Animation from a Single Photo

Chung-Yi Weng (University of Washington)*:

Brian Curless (University of Washington): http://homes.cs.washington.edu/~curless/

Ira Kemelmacher-Shlizerman (University of Washington + Facebook):

【Computational photography】Learning to Light for Mobile Mixed Reality in Unconstrained Environments

Chloe Le Gendre (Google Inc.)*:

Wan-Chun Alex Ma (Google Inc.):

Graham Fyffe (Google Inc.):

John P Flynn (Google Inc):

Laurent Charbonnel (Google Inc.):

Jay Busch (Google Inc.):

Paul E Debevec (Google VR):

【Computational photography】Iterative Residual CNNs for Burst Photography Applications

Filippos Kokkinos (Skolkovo Institute of Science and Technology)*:

Stamatis Lefkimmiatis (Skolkovo Institute of Science and Technology):

【Computational photography】Turn a Silicon Camera into an In Ga As Camera

Feifan Lv (Beihang University):

Yinqiang Zheng (National Institute of Informatics): https://researchmap.jp/yinqiangzheng

Bo Han Zhang (Beihang University):

Feng Lu (Beihang University)*:

【Computational photography】Fast and Flexible Indoor Scene Synthesis with Deep Convolutional Generative Models

Daniel Ritchie (Brown University)*:

Kai Wang (Brown University):

Yu-An Lin (Brown University):

【Computational photography】Reflective and Fluorescent Separation under Narrow-Band Illumination

Koji Koyamatsu (Kyushu Institute of Technology):

Daichi Hidaka (Kyushu Institute of Technology):

Takahiro Okabe (Kyushu Institute of Technology)*:

Hendrik P. A. Lensch (University of Tübingen):

【Computational photography】Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss

Lele Chen (University of Rochester)*:

Ross Maddox (University of Rochester):

Zhiyao Duan (Unversity of Rochester):

Chenliang Xu (University of Rochester): http://www.cs.rochester.edu/~cxu22/

【Computational photography】From One Photon to a Billion: High Flux Imaging with Single-Photon Sensors

Atul N Ingle (University of Wisconsin-Madison)*:

Andreas Velten (University of Wisconsin – Madison):

Mohit Gupta (“University of Wisconsin-Madison, USA “): http://wisionlab.cs.wisc.edu/people/mohit-gupta/

【Computational photography】Photon-Flooded Single-Photon 3D Cameras

Anant Gupta (University of Wisconsin Madison)*:

Atul N Ingle (University of Wisconsin-Madison):

Andreas Velten (University of Wisconsin – Madison):

Mohit Gupta (“University of Wisconsin-Madison, USA “): http://wisionlab.cs.wisc.edu/people/mohit-gupta/

【Computational photography】Acoustic Non-Line-of-Sight Imaging

David Lindell (Stanford University)*:

Gordon Wetzstein (Stanford University):

Vladlen Koltun (Intel Labs): http://vladlen.info/publications/

【Computational photography】Steady-state Non-Line-of-Sight Imaging

Wenzheng Chen (University of Toronto):

Simon Daneau (Algolux)*:

Colin Brosseau (Algolux):

Felix Heide (Princeton University):

【Computational photography】End-to-end Projector Photometric Compensation

Bingyao Huang (Temple University)*:

Haibin Ling (Temple University): http://www.dabi.temple.edu/~hbling/

【Computational photography】Bringing a Blurry Frame Alive at High Frame-Rate with an Event Camera

Liyuan Pan (The Australian National University)*:

cedric scheerlinck (The Australian National University):

RICHARD HARTLEY (Australian National University, Australia):

Miaomiao Liu (The Australian National University):

Yuchao Dai (Northwestern Polytechnical University):

Xin Yu (Australian National University):

【Computational photography】Bringing Alive Blurred Moments!

Kuldeep Purohit (Indian Institute of Technology Madras)*:

Anshul Shah (University of Maryland, College Park):

Rajagopalan N Ambasamudram (Indian Institute of Technology Madras):

【Computational photography】Learning to Synthesize Motion Blur

Tim Brooks (Google)*:

Jonathan T Barron (Google Research):

【Computational photography】Underexposed Photo Enhancement using Deep Illumination Estimation

Ruixing Wang (The Chinese University of Hong Kong):

Qing Zhang ( Sun Yat-sen University):

Chi-Wing Fu (The Chinese University of Hong Kong):

Xiaoyong Shen (Tencent):

WEI-SHI ZHENG (Sun Yat-sen University, China)*:

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Computational photography】Total Scene Capture: Neural Rerendering in the Wild

Moustafa Meshry (University of Maryland)*:

Ricardo Martin-Brualla (Google):

Noah Snavely (Cornell University and Google AI): http://www.cs.cornell.edu/~snavely/

Hugues Hoppe (Google Inc.):

Sameh Khamis (Google):

Rohit Pandey (Google):

Dan B Goldman (Google, Inc.):

【Computational photography】Fast Spatially-Varying Indoor Lighting Estimation

Mathieu Garon (Université Laval):

Kalyan Sunkavalli (Adobe Research): http://www.eecs.harvard.edu/~kalyans/

Nathan Carr (Adobe):

Sunil Hadap (Adobe):

Jean-Francois Lalonde (Université Laval)*: http://vision.gel.ulaval.ca/~jflalonde/

【Computational photography】Neural Illumination: Lighting Prediction for Indoor Environments

Shuran Song (Princeton)*:

Thomas Funkhouser (Princeton University and Google, Inc.):

【Computational photography】Deep Sky Modeling for Single Image Outdoor Lighting Estimation

Yannick Hold-Geoffroy (Adobe Research)*:

Akshaya Athwale (Indian Institute of Technology Dhanbad):

Jean-Francois Lalonde (Université Laval): http://vision.gel.ulaval.ca/~jflalonde/

【Computational photography】Depth-attentional Features for Single-image Rain Removal

Xiaowei Hu (The Chinese University of Hong Kong)*:

Chi-Wing Fu (The Chinese University of Hong Kong):

Lei Zhu (The Chinese University of Hong Kong):

Pheng-Ann Heng (The Chinese Univsersity of Hong Kong): http://www.cse.cuhk.edu.hk/~pheng/

【Computational photography】On Finding Gray Pixel

Yanlin Qian (Tampere University of Technology)*:

Joni-Kristian Kamarainen (Tampere University):

jarno nikkanen (Intel Finland):

Jiri Matas (CMP CTU FEE):

【Computational photography】Learning Transformation Synchronization

Xiangru Huang (University of Texas at Austin):

Zhenxiao Liang (The University of Texas at Austin):

Xiaowei Zhou (Zhejiang Univ., China):

Yao Xie (Georgia Tech):

Qixing Huang (The University of Texas at Austin)*:

Leonidas Guibas (Stanford University):

【Computational photography】Natural and Realistic Single Image Super-Resolution with Explicit Natural Manifold Discrimination

Jae Woong Soh (Seoul National University)*:

Gu Yong Park (Seoul National University):

Junho Jo (Seoul National University):

Nam Ik Cho (Seoul National University):

【Computational photography】Fast Single Image Reflection Suppression via Convex Optimization

Yang Yang (Tencent AI Lab)*:

Wenye Ma (Tencent):

Yin Zheng (Tencent AI Lab):

Jian-Feng Cai (Hong Kong University of Science and Technology):

Weiyu Xu (University of Iowa):

【Computational photography】Enhanced Pix2pix Dehazing Network

Yanyun Qu (XMU)*:

Yizi Chen (XMU):

Jingying Huang (XMU):

Yuan Xie (East China Normal University):

【Computational photography】Assessing Personally Perceived Image Quality via Image Features and Collaborative Filtering

Jari Korhonen (Shenzhen University)*:

【Computational photography】Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements

Kaixuan Wei (Beijing Institute of Technology):

Jiaolong Yang (Microsoft Research Asia)*:

Ying Fu (Beijing Institute of Technology):

David Wipf (Microsoft Research Asia):

Hua Huang (Beijing Institute of Technology):

【Computational photography】Discovering Interpretable Fair Representations

Novi Quadrianto (University of Sussex / HSE)*:

Viktoriia Sharmanska (Imperial College London):

Oliver Thomas (University of Sussex):

【Computational photography】World from Blur

Jiayan Qiu (University of Sydney)*:

Xinchao Wang (Stevens Institute of Technology):

Stephen J Maybank (Birkbeck College):

Dacheng Tao (University of Sydney):

【Computational photography】Sparse Fool: a few pixels make a big difference

Apostolos Modas (EPFL)*:

Seyed-Mohsen Moosavi-Dezfooli (EPFL):

Pascal Frossard (EPFL):

【Computational photography】Effective Aesthetics Prediction with Multi-level Spatially Pooled Features

Vlad Hosu (University of Konstanz)*:

Bastian Goldluecke (University of Konstanz):

Dietmar Saupe (University of Konstanz):

【Computational photography】Enhancing Diversity of Defocus Blur Detectors via Cross-Ensemble Network

Wenda Zhao (Dalian University of Technology)*:

Bowen Zheng (Dalian University of Technology):

Qiuhua Lin (Dalian University of Technology):

Huchuan Lu (Dalian University of Technology): http://ice.dlut.edu.cn/lu/index.html

【Computational photography】3D Appearance Super-Resolution with Deep Learning

Yawei Li (ETH Zurich)*:

Vagia Tsiminaki (ETH Zurich):

Radu Timofte (ETH Zurich):

Marc Pollefeys (ETH Zurich / Microsoft): http://www.inf.ethz.ch/personal/pomarc/

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Computational photography】Automatic Face Aging in Videos via Deep Reinforcement Learning

Chi Nhan Duong ( Concordia University)*:

Khoa Luu (University of Arkansas):

Kha Gia Quach (Concordia University):

Nghia H Nguyen (University of Arkansas):

Eric Patterson (Clemson University):

Tien D Bui (Concordia):

Ngan Le (Carnegie Mellon University):

【Computational photography】Learning Image and Video Compression through Spatial-Temporal Energy Compaction

Zhengxue Cheng (Waseda University)*:

Heming Sun (Waseda University, Japan):

Masaru Takeuchi (Waseda University):

Jiro Katto (Waseda University):

【Computational photography】Event-based High Dynamic Range Image and Very High Frame Rate Video Generation using Conditional Generative Adversarial Networks

  1. Mohammad Mostafavi I. (GIST):

Lin Wang (KAIST):

Yo-Sung HO (GIST):

Kuk-Jin Yoon (KAIST)*: https://cvl.gist.ac.kr/introduction.html

【Computational photography】Capture, Learning, and Synthesis of 3D Speaking Styles

Daniel Cudeiro (Max Planck Institute for Intelligent Systems):

Timo Bolkart (Max Planck Institute for Intelligent Systems):

Cassidy Laidlaw (Max Planck Institute for Intelligent Systems):

Anurag Ranjan (MPI for Intelligent Systems):

Michael J. Black (Max Planck Institute for Intelligent Systems)*: http://ps.is.tue.mpg.de/person/black

【Computational photography】Ray-Space Projection Model for Light Field Camera

Qi Zhang (Northwestern Polytechnical University):

Jinbo Ling (Northwestern Polytechnical University):

Qing Wang (Northwestern Polytechnical University)*:

Jingyi Yu (Shanghai Tech University):

【Computational photography】Hyperspectral Imaging with Random Printed Mask

Yuanyuan Zhao (Nanjing University):

Hui Guo (Nanjing University):

Zhan Ma (Nanjing University):

Xun Cao (Nanjing University):

Tao Yue (Nanjing University):

Xuemei Hu (Nanjing University)*:

【Computational photography】All-Weather Deep Outdoor Lighting Estimation

Jinsong Zhang (Université Laval):

Kalyan Sunkavalli (Adobe Research): http://www.eecs.harvard.edu/~kalyans/

Yannick Hold-Geoffroy (Adobe Research):

Sunil Hadap (Adobe):

Jonathan Eisenman (Adobe Systems):

Jean-Francois Lalonde (Université Laval)*: http://vision.gel.ulaval.ca/~jflalonde/

【Computational photography】Inverse Cooking: Recipe Generation from Food Images

Amaia Salvador (Universitat Politècnica de Catalunya)*:

Michal Drozdzal (FAIR):

Xavier Giro-i-Nieto (Universitat Politecnica de Catalunya):

Adriana Romero (FAIR):

【Computational photography】Robust Histopathology Image Analysis: to Label or to Synthesize?

Le Hou (Stony Brook University)*:

Ayush Agarwal (Stanford University):

Dimitris Samaras (Stony Brook University): http://www3.cs.stonybrook.edu/~samaras/

Tahsin Kurc (Stony Brook University):

Rajarsi Gupta (Stony Brook University):

Joel Saltz (Stony Brook University):

【Computational photography】Image Generation from Layout

Bo Zhao (University of British Columbia)*:

Lili Meng (University of British Columbia):

Weidong Yin (University of British Columbia):

Leonid Sigal (University of British Columbia): https://www.cs.ubc.ca/~lsigal/

【Computational photography】Practical Full Resolution Learned Lossless Image Compression

Fabian Mentzer (ETH Zurich)*:

Eirikur Agustsson (ETH Zurich):

Michael Tschannen (ETH Zurich):

Radu Timofte (ETH Zurich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Computational photography】Constrained Generative Adversarial Networks for Interactive Image Generation

Eric Heim (AFRL/RI)*:

【Computational photography】Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks

Seungjoo Yoo (Korea University):

Hyojin Bahng (Korea University):

Sunghyo Chung (Korea University):

junsoo lee (Naver Webtoon):

Jaehyuk Chang (NAVER Webtoon Corp):

Jaegul Choo (Korea University)*: http://davian.korea.ac.kr/

【Computational photography】PMS-Net: Robust Haze Removal Based on Patch Map for Singe Images

Wei-Ting Chen (National Taiwan University)*:

Jian-Jiun Ding (Nil):

Sy-Yen Kuo (National Taiwan University):

【Computational photography】Re-Identification Supervised 3D Texture Generation

Jian Wang (State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences)*:

Yunshan Zhong (Peking University):

Yachun Li (Zhejiang University):

Chi Zhang (Megvii Inc.):

Yichen Wei (Megvii Research Shanghai):

【Computational photography】Object-driven Text-to-Image Synthesis via Adversarial Training

Wenbo Li (“University at Albany, SUNY”)*:

Pengchuan Zhang (Microsoft Research AI):

Lei Zhang (Microsoft Research): http://www4.comp.polyu.edu.hk/~cslzhang/

Qiuyuan Huang (Microsoft Research AI):

Xiaodong He (JD AI Research):

Siwei Lyu (University at Albany): http://www.cs.albany.edu/~lsw/

Jianfeng Gao (Microsoft Research):

【Computational photography】Spectral Reconstruction from Dispersive Blur: Approaching Full Light Throughput Spectral Imager

Yuanyuan Zhao (Nanjing University):

Hui Guo (Nanjing University):

Xun Cao (Nanjing University):

Zhan Ma (Nanjing University):

Tao Yue (Nanjing University):

Xuemei Hu (Nanjing University)*:

【Computational photography】Quasi-Unsupervised Color Constancy

Simone Bianco (University of Milano Bicocca)*:

Claudio Cusano (University of Pavia):

【Computational photography】DVC: An End-to-end Deep Video Compression Framework

Guo Lu (Shanghai Jiao Tong University)*:

Wanli Ouyang (The University of Sydney): http://www.ee.cuhk.edu.hk/~wlouyang/

Dong Xu (University of Sydney): http://www.ntu.edu.sg/home/dongxu/

Chunlei Cai (Shanghai Jiao Tong University):

Xiaoyun Zhang (Shanghai Jiao Tong University):

Zhiyong Gao (Shanghai Jiao Tong University):

【Computational photography】“Double-DIP”: Unsupervised Image Decomposition via Coupled Deep-Image-Priors

Yosef Gandelsman (Weizmann Institute of Science)*:

Assaf Shocher (Weizmann Institute of Science):

Michal Irani (Weizmann Institute, Israel): http://www.wisdom.weizmann.ac.il/~irani/

【Computational photography】Focus Loss Functions for Event-based Vision

Guillermo Gallego (University of Zurich and ETH Zurich)*:

Mathias Gehrig (University of Zurich):

Davide Scaramuzza (University of Zurich & ETH Zurich, Switzerland): http://rpg.ifi.uzh.ch/people_scaramuzza.html

【Computational photography】Dichromatic Model Based Temporal Color Constancy for AC Light Sources

Jun-Sang Yoo (Korea University)*:

Jong-Ok Kim (Korea University):

【Deep learning】Edge-Labeling Graph Neural Network for Few-shot Learning

Jongmin Kim (KAIST)*:

Taesup Kim (Université de Montréal):

Sungwoong Kim (Kakao Brain):

Chang D. Yoo (KAIST): http://slsp.kaist.ac.kr/xe/index.php?mid=home

【Deep learning】Generating Classification Weights with Graph Neural Networks for Few-Shot Learning

Spyros Gidaris (valeo.ai)*:

Nikos Komodakis (“ENPC, France”): http://imagine.enpc.fr/~komodakn/

【Deep learning】Kervolutional Neural Networks

Chen Wang (Nanyang Technological University)*:

JIANFEI YANG (Nanyang Technological University):

Prof. Dr. Respected Colleauge (IJCAS Editorial Member):

Junsong Yuan (“State University of New York at Buffalo, USA”): https://cse.buffalo.edu/~jsyuan/

【Deep learning】Why Re Lu networks yield high-confidence predictions far away from the training data and how to mitigate the problem

Matthias Hein (University of Tuebingen)*:

Maksym Andriushchenko (Saarland University):

Julian Bitterwolf (University of Tuebingen):

【Deep learning】On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions

Yusuke Tsuzuku (The University of Tokyo/RIKEN)*:

Issei Sato (The university of Tokyo/RIKEN):

【Deep learning】Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization

Siyuan Qiao (Johns Hopkins University)*:

Zhe Lin (Adobe Research): http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Jianming Zhang (Adobe Research):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Deep learning】Hardness-Aware Deep Metric Learning

Wenzhao Zheng (Tsinghua University):

Zhaodong Chen (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【Deep learning】Learning to Learn Loss for Active Learning

Donggeun Yoo (Lunit)*:

In So Kweon (KAIST): http://rcv.kaist.ac.kr/

【Deep learning】Striking the Right Balance with Uncertainty

Salman Khan (Australian National University (ANU)):

Munawar Hayat (University of Canberra):

Waqas Zamir (IIAI):

Jianbing Shen (Beijing Institute of Technology)*: http://cs.bit.edu.cn/shenjianbing/

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Deep learning】Auto Augment: Learning Augmentation Strategies from Data

Ekin D Cubuk (Google Brain)*:

Barret Zoph (Google):

Dandelion Mane (Protocol Labs):

Vijay Vasudevan (Google Brain):

Quoc Le (Google Brain):

【Deep learning】Large Scale Incremental Learning

Yue Wu (northeastern university)*:

Yinpeng Chen (Microsoft):

Lijuan Wang (Microsoft):

Yuancheng Ye (CCNY):

Zicheng Liu (Microsoft):

Yandong Guo (MSR):

YUN FU (Northeastern University): http://www1.ece.neu.edu/~yunfu/

【Deep learning】Meta-Transfer Learning for Few-Shot Learning

Qianru Sun (MPI)*:

Yaoyao Liu (Tianjin University):

Tat-Seng Chua (National Univ. of Singapore):

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

【Deep learning】Graph-Based Global Reasoning Networks

Yunpeng Chen (National University of Singapore):

Yannis Kalantidis (Facebook Research)*:

Marcus Rohrbach (Facebook AI Research):

Zhicheng Yan (Facebook AI):

Yan Shuicheng (National University of Singapore):

Jiashi Feng (NUS): https://sites.google.com/site/jshfeng/

【Deep learning】SSN: Learning Sparse Switchable Normalization via Sparsest Max

Wenqi Shao (The Chinese University of Hong Kong)*:

Tianjian Meng (University of Pittsburgh):

Jingyu Li (Sense Time Research):

Ruimao Zhang (The Chinese University of Hong Kong):

Yudian Li (Sense Time):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Ping Luo (The Chinese University of Hong Kong):

【Deep learning】Task-Aware Synthetic Data Generation

Shashank Tripathi (Carnegie Mellon University):

Siddhartha Chandra (Amazon):

Ambrish Tyagi (Amazon):

James Rehg (Georgia Institute of Technology): http://www.cc.gatech.edu/~rehg/

Visesh Chari (Amazon Lab126)*:

Amit Agrawal (Amazon):

Kris Kitani (CMU):

【Deep learning】Selective Kernel Networks

Xiang Li (Nanjing University of Science and Technology)*:

Xiaolin Hu (Tsinghua University):

Wenhai Wang (Nanjing university):

Jian Yang (Nanjing University of Science and Technology):

【Deep learning】On Implicit Filter Level Sparsity in Convolutional Neural Networks

Dushyant Mehta (MPI Informatics)*:

Kwang In Kim (UNIST):

Christian Theobalt (MPI Informatik):

【Deep learning】Learning Channel-wise Interactions for Binary Convolutional Neural Networks

Ziwei Wang (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Chenxin Tao (Tsinghua University):

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Deep learning】Semantic Regeneration Network

Yi Wang (Chinese University of Hong Kong)*:

Xin Tao (Tencent):

Xiaoyong Shen (Tencent):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【Deep learning】Searching for A Robust Neural Architecture in Four GPU Hours

Xuanyi Dong (UTS)*:

Yi Yang (UTS): http://www.cs.cmu.edu/~yiyang/

【Deep learning】Adaptively-Connected Neural Network

Guangrun Wang (Sun Yat-sen University)*:

Keze Wang (University of California, Los Angeles):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

【Deep learning】Factor Graph Attention

Idan Schwartz (Technion)*:

Seunghak Yu (Samsung Research):

Tamir Hazan (Technion):

Alexander Schwing (UIUC): http://www.alexander-schwing.de/

【Deep learning】Understanding the Disharmony between Dropout and Batch Normalization by Variance Shift

Xiang Li (Nanjing University of Science and Technology)*:

Shuo Chen (Nanjing University of Science and Technology):

Xiaolin Hu (Tsinghua University):

Jian Yang (Nanjing University of Science and Technology):

【Deep learning】Circulant Binary Convolutional Networks: Enhancing the Performance of 1-bit DCNNs with Circulant Back Propagation

Chunlei Liu (Beihang University):

Wenrui Ding (Beihang University):

Xin Xia (Beihang University):

Baochang Zhang (Beihang University):

Jiaxin Gu (Beihang University):

Jianzhuang Liu (Noah’s Ark Lab, Huawei Technologies Company, Ltd., China):

Rongrong Ji (Xiamen University, China)*:

David Doermann (University at Buffalo):

【Deep learning】Virtual Networks for Memory Efficient Inference of Multiple Tasks

Eunwoo Kim (University of Oxford):

Chanho Ahn (Department of ECE and ASRI, Seoul National University):

Philip Torr (University of Oxford): http://www.robots.ox.ac.uk/~tvg/

Songhwai Oh (Seoul National University)*:

【Deep learning】Variational Convolutional Neural Network Pruning

Chenglong Zhao (Shanghai Jiao Tong University):

Bingbing Ni (Shanghai Jiao Tong University)*:

Jian Zhang (Shanghai Jiaotong University):

Qiwei Zhao (Shanghai Jiao Tong University):

Wenjun Zhang (Shanghai Jiao Tong University):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Deep learning】Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression

Yuchao Li (Xiamen University):

Shaohui Lin (Xiamen University):

Baochang Zhang (Beihang University):

Jianzhuang Liu (Noah’s Ark Lab, Huawei Technologies Company, Ltd., China):

David Doermann (University at Buffalo):

Yongjian Wu (Tencent Technology (Shanghai) Co.,Ltd):

Feiyue Huang (Tencent):

Rongrong Ji (Xiamen University, China)*:

【Deep learning】Mnas Net: Platform-Aware Neural Architecture Search for Mobile

Mingxing Tan (Google Brain)*:

Bo Chen (Google):

Ruoming Pang (Google Brain):

Vijay Vasudevan (Google Brain):

Mark Sandler (Google):

Andrew Howard (Google):

Quoc Le (Google Brain):

【Deep learning】Gradient Matching Generative Networks for Zero-Shot Learning

Mert Bulent Sariyildiz (Bilkent University)*:

Ramazan Gokberk Cinbis (METU):

【Deep learning】ELASTIC: Improving CNNs by Instance Specific Scaling Policies

Huiyu Wang (Johns Hopkins University)*:

Aniruddha Kembhavi (Allen Institute for Artificial Intelligence):

Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence): http://homes.cs.washington.edu/~ali/index.html

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

Mohammad Rastegari (Allen Institute for Artificial Intelligence):

【Deep learning】C2AE: Class Conditioned Auto-Encoder for Open-set Recognition

Poojan B Oza (Johns Hopkins University)*:

Vishal Patel (Johns Hopkins University):

【Deep learning】Learning Metrics from Teachers: Compact Networks for Image Embedding

Lu Yu (CVC)*:

Vacit Oguz Yazici (CVC/Wide-Eyes Technologies):

Xialei Liu (Computer Vision Center Barcelona):

Joost van de Weijer (Computer Vision Center):

Yongmei Cheng (NWPU):

Arnau Ramisa (Wide-Eyes Technologies):

【Deep learning】Global Second-order Pooling Convolutional Networks

Zilin Gao (Dalian University of Technology):

Jiangtao Xie (Dalian University of Technology):

Qilong Wang (Tianjin University):

Peihua Li (Dalian University of Technology)*:

【Deep learning】4D Spatio-Temporal Conv Net: Minkowski Convolutional Neural Network

Christopher Choy (Stanford University)*:

Jun Young Gwak (Stanford University):

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

【Deep learning】Learning Spatial Common Sense with Geometry-Aware Recurrent Networks

Hsiao-Yu Tung (Carnegie Mellon University)*:

Ricson Cheng (Carnegie Mellon University):

Katerina Fragkiadaki (Carnegie Mellon University):

【Deep learning】Compressing Convolutional Neural Networks via Factorized Convolutional Filters

Tuanhui Li (Tsinghua University):

Baoyuan Wu (Tencent AI Lab)*:

Yujiu Yang (Tsinghua Univ.):

Yanbo Fan (Tencent AI Lab):

Yong Zhang (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Deep learning】Deep MDS: Non-Linear Projection of Deep Representations

Gong Sixue (Michigan State University):

Vishnu Boddeti (Michigan State University)*:

Anil Jain (Michigan State University):

【Deep learning】Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration

Yang He (University of Technology Sydney)*:

Ping Liu (UTS):

Ziwei Wang (Information Science Academy, CETC):

Zhilan Hu (Huawei):

Yi Yang (University of Technology, Sydney): http://www.cs.cmu.edu/~yiyang/

【Deep learning】Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss

Sangil Jung (Samsung)*:

Changyong Son (Samsung):

Seohyung Lee (Samsung):

Jinwoo Son (Samsung):

Jae-Joon Han (Samsung):

Youngjun Kwak (Samsung):

Sung Ju Hwang (KAIST):

Changkyu Choi (Samsung):

【Deep learning】Sensitive-Sample Fingerprinting of Deep Neural Networks

Zecheng He (Princeton University)*:

Tianwei Zhang (Princeton University):

Ruby Lee (Princeton University):

【Deep learning】Local to Global Learning for Deep Neural Networks

Hao Cheng (Shanghaitech University)*:

Dongze Lian (Shanghaitech University):

Bowen Deng (Shanghaitech University):

Shenghua Gao (Shanghaitech University):

Tao Tan (Eindhoven University of Technology):

Yanlin Geng (Xidian University):

【Deep learning】RENAS: Reinforced Evolutionary Neural Architecture Search

Yukang Chen (Institute of Automation, Chinese Academy of Sciences):

Gaofeng Meng (Chinese Academy of Sciences): http://www.escience.cn/people/menggaofeng/index.html

Qian Zhang (Horizon Robotics):

SHIMING XIANG (Chinese Academy of Sciences, China):

Chang Huang (Horizon Robotics):

Lisen Mu (Horizon Robotics LTD):

Xinggang Wang (Huazhong Univ. of Science and Technology)*: http://www.xinggangw.info/

【Deep learning】Co-Occurrence Neural Network

Irina Shevlev (Tel Aviv University)*:

Shai Avidan (Tel Aviv University):

【Deep learning】Het Conv: Heterogeneous Kernel-Based Convolutions for Deep CNNs

Pravendra Singh (Indian Institute of Technology Kanpur):

Vinay Kumar Verma (Indian Institute of Technology Kanpur):

Piyush Rai (IIT Kanpur):

Vinay P Namboodiri (IIT Kanpur)*:

【Deep learning】Instance-Level Meta Normalization

Songhao Jia (National Tsing Hua University):

Ding-Jie Chen (Academia Sinica):

Hwann-Tzong Chen (National Tsing Hua University)*: http://www.cs.nthu.edu.tw/~htchen/

【Deep learning】Iterative Normalization: Beyond Standardization towards Efficient Whitening

Lei Huang (the inception institute of artificial intelligence)*:

Yi Zhou (Inception Institute of Artificial Intelligence):

Fan Zhu (Inception Institute of Artificial Intelligence):

Li Liu (the inception institute of artificial intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Deep learning】Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?

Shilin Zhu (UCSD)*:

Xin Dong (Harvard Univeristy):

Hao Su (UCSD):

【Deep learning】Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure

Xiaohan Ding (Tsinghua University)*:

guiguang ding (Tsinghua University, China):

Yuchen Guo (Tsinghua University):

Jungong Han (Lancaster University):

【Deep learning】Knockoff Nets: Stealing Functionality of Black-Box Models

Tribhuvanesh Orekondy (Max Planck Institute for Informatics)*:

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

Mario Fritz (CISPA Helmholtz Center for Information Security): https://scalable.mpi-inf.mpg.de/

【Deep learning】Deep Embedding Learning with Discriminative Sampling Policy

Yueqi Duan (Tsinghua University):

Lei Chen (Tianjin University):

Jiwen Lu (Tsinghua University)*:

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【Deep learning】Deep Global Generalized Gaussian Networks

Qilong Wang (Tianjin University)*:

Peihua Li (Dalian University of Technology):

Qinghua Hu (Tianjin University):

Pengfei Zhu (tianjin university):

Wangmeng Zuo (Harbin Institute of Technology, China):

【Deep learning】Dynamic Recursive Neural Network

Qiushan Guo (Beijing University of Posts and Telecommunications)*:

Zhipeng Yu (Sensetime Group Limited):

Yichao Wu (Sensetime Group Limited):

Ding Liang (Sensetime Group Limited):

Haoyu Qin (Sensetime):

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

【Deep learning】Efficient Multi-Domain Learning by Covariance Normalization

Yunsheng Li (UCSD)*:

Nuno Vasconcelos (UC San Diego): http://www.svcl.ucsd.edu/

【Deep learning】On the Continuity of Rotation Representation in Neural Networks

Yi Zhou (University of Southern California)*:

Connelly Barnes (University of Virginia):

Jingwan Lu (Adobe Research):

Jimei Yang (Adobe): https://eng.ucmerced.edu/people/jyang44

Hao Li (Pinscreen/University of Southern California/USC ICT): https://www.hao-li.com/Hao_Li/Hao_Li_-_about_me.html

【Deep learning】Interpreting CNNs via Explanatory Trees

Quanshi Zhang (Shanghai Jiao Tong University)*:

Yu Yang (UCLA):

Haotian Ma (Southern University of Science and Technology):

Ying Nian Wu (University of California, Los Angeles):

【Deep learning】OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks

Jiashi Li (Beijing University of Posts and Telecommunications)*:

Jingyu Wang (Beijing University of Posts and Telecommunications):

Qi Qi (Beijing University of Posts and Telecommunications):

Ce Ge (Beijing University of Posts and Telecommunications):

Yujian Li (Beijing University of Posts and Telecommunications):

Zhangzhang Yue (Beijing University of Posts and Telecommunications):

Haifeng Sun (Beijing University of Posts and Telecommunications):

【Deep learning】Accelerating Convolutional Neural Networks via Activation Map Compression

Georgios Georgiadis (Samsung)*:

【Deep learning】Variational Bayesian Dropout

Yuhang Liu (Wuhan University):

Wenyong Dong (Wuhan University)*:

Lei Zhang (The University of Adelaide): http://www4.comp.polyu.edu.hk/~cslzhang/

Dong Gong (The University of Adelaide):

Qinfeng Shi (University of Adelaide): https://cs.adelaide.edu.au/~javen/

【Deep learning】Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction

Osama Makansi (University of Freiburg)*:

Eddy Ilg (University of Freiburg):

Özgün Çiçek (University of Freiburg):

Thomas Brox (University of Freiburg): http://lmb.informatik.uni-freiburg.de/people/brox/index.en.html

【Deep learning】A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks

Yinghao Xu (Zhejiang University)*:

Xin Dong (Harvard Univeristy):

Yudian Li (None):

Hao Su (UCSD):

【Deep learning】Panoptic Feature Pyramid Network

Alexander Kirillov (Facebook AI Reserach)*:

Kaiming He (Facebook AI Research): http://research.microsoft.com/en-us/um/people/kahe/

Ross Girshick (FAIR): http://www.cs.berkeley.edu/~rbg/

Piotr Dollar (FAIR): http://vision.ucsd.edu/~pdollar/

【Deep learning】Quantization Networks

Jiwei Yang (University of Science and Technology of China):

Xu Shen (Alibaba Group):

Jun Xing (mi Ho Yo):

Xinmei Tian (USTC)*:

Houqiang Li (University of Science and Technology of China):

Bing Deng (Damo Academy, Alibaba Group):

Jianqiang Huang (Alibaba Group):

Xiansheng Hua (Damo Academy, Alibaba Group):

【Deep learning】Domain Specific Batch Normalization for Unsupervised Domain Adaptation

Woong-Gi Chang (POSTECH)*:

Tackgeun You (POSTECH):

Seonguk Seo (Seoul National University):

Suha Kwak (POSTECH):

Bohyung Han (Seoul National University): http://cvlab.postech.ac.kr/~bhhan/

【Deep learning】T-Net: High-Order Tensor FCN

Jean Kossaifi (Imperial College London)*:

Adrian Bulat (University of Nottingham):

Georgios Tzimiropoulos (University of Nottingham): http://www.cs.nott.ac.uk/~pszyt/

Maja Pantic (Imperial College London / Samsung ): http://ibug.doc.ic.ac.uk/research

【Deep learning】Cross Domain Model Compression by Structured Weight Sharing

Shangqian Gao (University of Pittsburgh)*:

Cheng Deng (Xidian University):

Heng Huang (University of Pittsburgh):

【Deep learning】Transferable Auto ML by Model Sharing over Grouped Datasets

Xue Chao (IBM Research)*:

Junchi Yan (Shanghai Jiao Tong University):

Rong Yan (IBM ):

Stephen M Chu (IBM Research – China):

Yonghua Lin (IBM):

Yonggang Hu (IBM):

【Deep learning】Learning Not to Learn: Training Deep Neural Networks with Biased Data

Byungju Kim (KAIST)*:

Hyunwoo Kim (Beijing Institute of Technology):

Kyungsu Kim (samsung research):

Sungjin Kim (SAMSUNG ELECTRONICS CO.,LTD):

Junmo Kim (KAIST):

【Deep learning】Fully Learnable Group Convolution for Acceleration of Deep Neural Networks

Xijun Wang (Institute of Computing Technology, Chinese Academy of Sciences):

Meina Kan (Institute of Computing Technology, Chinese Academy of Sciences)*:

Shiguang Shan (Chinese Academy of Sciences): http://vipl.ict.ac.cn/members/sgshan

Xilin Chen (China):

【Deep learning】EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch

Jian Ren (Rutgers University)*:

Zhe Li (The University of Iowa ):

Jianchao Yang (Snapchat): http://www.ifp.illinois.edu/~jyang29/

Ning Xu (Snap Inc):

Tianbao Yang (University of Iowa): http://homepage.divms.uiowa.edu/~tyng/

David Foran (Rutgers Cancer Institute of New Jersey):

【Deep learning】Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks

Jörg Wagner (Bosch Center for Artificial Intelligence)*:

Jan Mathias Koehler (Bosch Center for Artificial Intelligence):

Tobias Gindele (Robert Bosch Gmb H):

Leon Hetzel (Bosch Center for Artificial Intelligence):

Jakob Thaddaeus Wiedemer (Bosch Center for Artificial Intelligence):

Sven Prof. Behnke (University of Bonn):

【Deep learning】Structured Pruning of Neural Networks with Budget-Aware Regularization

Carl Lemaire (Universite de Sherbrooke)*:

Andrew Achkar (Miovision Technologies Inc., Canada):

Pierre-Marc Jodoin (Universite de Sherbrooke):

【Deep learning】MBS: Macroblock Scaling for CNN Model Reduction

Yu-Hsun Lin (CTBC Bank)*:

Chun-Nan Chou (HTC Research):

Edward Chang ():

【Deep learning】Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search

Xin Li (UISEE Company)*:

Yiming Zhou (University of Electrical Science and Technology of China):

Zheng Pan (UISEE Company):

Jiashi Feng (NUS): https://sites.google.com/site/jshfeng/

【Deep learning】Gater Net: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network

Zhourong Chen (The Hong Kong University of Science and Technology)*:

Yang Li (Google Research):

Samy Bengio (Google Brain):

Si Si (Google Research):

【Deep learning】ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

Sachin Mehta (University of Washington)*:

Mohammad Rastegari (Allen Institute for Artificial Intelligence):

Linda Shapiro (University of Washington): http://homes.cs.washington.edu/~shapiro/

Hannaneh Hajishirzi (University of Washington): https://homes.cs.washington.edu/~hannaneh/

【Deep learning】Propagation Mechanism for Deep and Wide Neural Networks

Dejiang Xu (National University of Singapore):

Mong Li Lee (National University of Singapore)*:

Wynne Hsu (National University of Singapore):

【Deep learning】Deformable Conv Nets v2: More Deformable, Better Results

Xizhou Zhu (University of Science and Technology of China):

Han Hu (Microsoft Research Asia):

Stephen Lin (Microsoft Research):

Jifeng Dai (Microsoft Research Asia)*:

【Deep learning】Kernel Transformer Networks for Compact Spherical Convolution

Yu-Chuan Su (UT Austin)*:

Kristen Grauman (Facebook AI Research & UT Austin): http://www.cs.utexas.edu/~grauman/

【Deep learning】Learning Personalized Modular Network Guided by Structured Knowledge

Xiaodan Liang (Sun Yat-sen University)*:

【Deep learning】Normalized Diversification

Shaohui Liu (Tsinghua University)*:

Xiao Zhang (University of Pennsylvania):

Jianqiao Q Wangni (University of Pennsylvania):

Jianbo Shi (University of Pennsylvania): http://www.cis.upenn.edu/~jshi/

【Deep learning】Re Pr: Improved Training of Convolutional Filters

Aaditya Prakash (Brandeis University)*:

James Storer (Brandeis University):

Dinei Florencio (Microsoft Research):

Cha Zhang (Microsoft Research):

【Deep learning】Cascaded Projection: End-to-End Network Compression and Acceleration

Breton L Minnehan (Rochester Institute of Technology)*:

Andreas Savakis (Rochester Institute of Technology):

【Deep learning】Deep Caps : Going Deeper with Capsule Networks

Jathushan Rajasegaran ( University of Moratuwa)*:

Vinoj Jayasundara (University of Moratuwa):

Sandaru Jayasekara (University of Moratuwa):

Hirunima Jayasekara (University of Moratuwa):

Ranga Rodrigo (University of Moratuwa):

Suranga Seneviratne (University of Sydney):

【Deep learning】DNASNet: Hardware-Aware Efficient Conv Net Design via Differentiable Neural Architecture Search

Bichen Wu (UC Berkeley)*:

Xiaoliang Dai (Princeton University):

Peizhao Zhang (Facebook):

Yanghan Wang (Facebook):

Fei Sun (Facebook):

Yiming Wu (Facebook):

Yuandong Tian (Facebook):

Peter Vajda (Facebook):

Yangqing Jia (Facebook): http://www.eecs.berkeley.edu/~jiayq/

Kurt Keutzer (EECS, UC Berkeley):

【Deep learning】So Deep: a Sorting Deep net to learn ranking loss surrogates

Martin Engilberge (Technicolor, Sorbonne universités)*:

Louis Chevallier (Technicolor):

Patrick Pérez (Valeo.ai):

Matthieu Cord (Sorbonne University):

【Deep learning】Pixel Adaptive Convolutional Neural Networks

Hang Su (University of Massachusetts, Amherst)*:

Varun Jampani (Nvidia Research):

Deqing Sun (NVIDIA): http://cs.brown.edu/~dqsun/index.html

Orazio Gallo (NVIDIA Research):

Erik Learned-Miller (University of Massachusetts, Amherst):

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【Deep learning】Single-frame Regularization for Temporally Stable CNNs

Gabriel Eilertsen (Linköping University)*:

Jonas Unger (Linköpings universitet):

Rafal Mantiuk (University of Cambridge):

【Deep learning】ECC: Energy Constrained Deep Neural Network Compression via a Bilinear Regression Model

Haichuan Yang (University of Rochester)*:

Yuhao Zhu (University of Rochester):

Ji Liu (University of Rochester):

【Deep learning】Seer Net: Predicting Convolutional Neural Network Feature-Map Sparsity through Low-Bit Quantization

Shijie Cao (Harbin Institute of Technology):

Lingxiao Ma (Peking University):

Wencong Xiao (Beihang University):

Chen Zhang (Microsoft Research Asia)*:

Yunxin Liu (MSRA):

lintao Zhang (Microsoft Research Asia):

Lanshun Nie (Harbin Institute of Technology):

Zhi Yang (Peking University):

【Deep learning】Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion

Ryutaro Tanno (University College London)*:

Ardavan Saeedi (Butterfly Network Inc):

Swami Sankaranarayanan (Butterfly Network Inc, New York, NY):

Daniel Alexander (University College London):

Nathan Silberman (Butterfly Network):

【Deep learning】Importance Estimation for Neural Network Pruning

Pavlo Molchanov (NVIDIA)*:

Arun Mallya (NVIDIA):

Stephen Tyree (NVIDIA):

Iuri Frosio (NVIDIA):

Jan Kautz (NVIDIA): https://research.nvidia.com/person/jan-kautz

【Deep learning】Building Efficient Deep Neural Networks with Unitary Group Convolutions

Ritchie Zhao (Cornell University)*:

Yuwei Hu (Cornell University):

Jordan A Dotzel (Cornell University):

Chris De Sa (Cornell):

Zhiru Zhang (Cornell Univeristy):

【Deep learning】Regularizing Activation Distribution for Training Binarized Deep Networks

Ruizhou Ding (Carnegie Mellon University)*:

Ting-Wu Chin (Carnegie Mellon University):

Diana Marculescu (Carnegie Mellon University):

Zeye Liu (Carnegie Mellon University):

【Deep learning】Robustness Verification of Classification Deep Neural Networks via Linear Programming

Wang Lin (Zhejiang Sci-Tech University):

Zhengfeng Yang (East China Normal University)*:

Xin Chen (Nanjing University):

Qingye Zhao (Nanjing University):

Xiangkun Li (East China Normal University):

Zhiming Liu (Southwest University):

Jifeng He (East China Normal University):

【Deep learning】Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network using Truncated Gaussian Approximation

Zhezhi He (University of Central Florida)*:

Deliang Fan (University of Central Florida):

【Deep learning】Hierarchical Disentanglement of Discriminative Latent Features for Zero-shot Learning

Bin Tong (Hitachi Ltd.)*:

Chao Wang (Ocean University of China):

Martin Klinkigt (Hitachi, Ltd.):

Yoshiyuki Kobayashi (Hitachi):

Yuichi Nonaka (Hitachi):

【Deep learning】Retrieval-augmented Convolutional Neural Networks against adversarial examples

Junbo Zhao (New York University)*:

Kyunghyun Cho (New York University):

【Deep learning】Progressive Ensemble Networks with Adaptive Label Embeddings for Zero Shot Recognition

Meng Ye (Temple University):

Yuhong Guo (Carleton University)*: http://www.cis.temple.edu/~yuhong/

【Deep learning】Atlas of Digital Pathology: A Generalized Hierarchical Histological Tissue Type-Annotated Database for Deep Learning

Mahdi S Hosseini (University of Toronto)*:

Gabriel Tse (University of Toronto):

Michael Tang (University of Toronto):

Jun Deng (University of Toronto):

Sajad Norouzi (University of Toronto):

Konstantinos N Plataniotis (Uof T):

Savvas Damaskinos (Huron Digital Pathology):

Corwyn Rowsell (st michael hospital):

Lyndon Chan (University of Toronto):

【Deep learning】Convolutional Neural Networks Deceived by Visual Illusions

Alexander Gomez Villa (Universitat Pompeu Fabra)*:

Adrian Martin (Universitat Pompeu Fabra):

Javier Vazquez-Corral (University of East Anglia):

Marcelo Bertalmío (Universitat Pompeu Fabra):

【Deep learning】Semantic Attribute Matching Networks

Seungryong Kim (Yonsei University)*:

Dongbo Min (Ewha Womans University):

Somi Jeong (Yonsei University):

Sunok Kim (Yonsei University):

Sangryul Jeon (Yonsei university):

Kwanghoon Sohn (Yonsei Univ.): http://diml.yonsei.ac.kr/professor.html

【Deep learning】Large-scale Distributed Second-order Optimization Using Kronecker-factored Approximate Curvature for Deep Convolutional Neural Networks

Kazuki Osawa (Tokyo Institute of Technology)*:

Yohei Tsuji (Tokyo Institute of Technology):

Yuichiro Ueno (Tokyo Institute of Technology):

Akira Naruse (NVIDIA):

Rio Yokota (Tokyo Institute of Technology):

Satoshi Matsuoka (RIKEN):

【Deep learning】Efficient Neural Network Compression

Hyeji Kim (Korea Advanced Institute of Science and Technology)*:

Muhammad Umar Karim Khan (Korea Advanced Institute of Science and Technology):

Chong-Min Kyung (Korea Advanced Institute of Science and Technology):

【Machine learning】Divide and Conquer the Embedding Space for Metric Learning

Artsiom O Sanakoyeu (Heidelberg University)*:

Vadim Tschernezki (Heidelberg University):

Uta Büchler (Heidelberg University):

Bjorn Ommer (Heidelberg University):

【Machine learning】Latent Space Autoregression for Novelty Detection

Davide Abati (University of Modena and Reggio Emilia)*:

Angelo Porrello (University of Modena and Reggio Emilia):

SIMONE CALDERARA (University of Modena and Reggio Emilia, Italy):

Rita Cucchiara (Universita Di Modena E Reggio Emilia): http://aimagelab.ing.unimore.it/imagelab/person.asp?idpersona=1

【Machine learning】Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks

Kuan Fang (Stanford Univeristy):

Alexander Toshev (Google)*:

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

【Machine learning】Feature-level Frankenstein: Eliminating Variations for Discriminative Recognition

Xiaofeng Liu (CMU)*:

B.V.K. Kumar (CMU):

Site Li (Carnegie Mellon University):

Ping Jia (Changchun Institute of Optics, Fine Mechanics and Physics):

Wanqing Xie (Harvard Medical School):

Jane You (HK Poly U):

Lingsheng Kong (Changchun Institute of Optics, Fine Mechanics and Physics):

【Machine learning】Learning a Unified Classifier Incrementally via Rebalancing

Saihui Hou (University of Science and Technology of China)*:

Xinyu Pan (MMLAB, CUHK):

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

Zilei Wang (University of Science and Technology of China):

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

【Machine learning】Temporal Cycle-Consistency Learning

Debidatta Dwibedi (Google)*:

Yusuf Aytar (Deep Mind):

Jonathan Tompson (Google):

Pierre Sermanet (Google):

Andrew Zisserman (University of Oxford): http://www.robots.ox.ac.uk/~vgg/

【Machine learning】TAFE-Net: Task-Aware Feature Embeddings for Efficient Learning and Inference

Xin Wang (UC Berkeley)*:

Fisher Yu (UC Berkeley):

Ruth Wang (UC Berkeley):

Trevor Darrell (UC Berkeley): http://www.eecs.berkeley.edu/~trevor/

Joseph Gonzalez (UC Berkeley):

【Machine learning】Attentive Single-tasking of Multiple Tasks

Kevis-Kokitsi Maninis (Eidgenössiche Technische Hochschule Zürich)*:

Ilija Radosavovic (Facebook AI Research):

Iasonas Kokkinos (UCL): http://cvn.ecp.fr/personnel/iasonas/index.html

【Machine learning】Fast AP: Deep Metric Learning to Rank

Kun He (Facebook Reality Labs)*:

Fatih Cakir (Boston University):

XIDE XIA (Boston University):

Brian Kulis (Boston University):

Stan Sclaroff (Boston University):

【Machine learning】End-to-End Multi-Task Learning with Attention

Shikun Liu (Imperial College London)*:

Edward Johns (Imperial College London):

Andrew Davison (Imperial College London):

【Machine learning】Self-Supervised Learning via Conditional Motion Propagation

Xiaohang Zhan (The Chinese University of Hong Kong)*:

Xingang Pan (The Chinese University of Hong Kong):

Ziwei Liu (The Chinese University of Hong Kong):

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

【Machine learning】Iterative Reorganization with Weak Spatial Constraints:Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning

Chen Wei (Peking University):

Lingxi Xie (Johns Hopkins University)*:

Xutong Ren (Peking University):

Yingda Xia (Johns Hopkins University):

Chi Su (Kingsoft Cloud):

Jiaying Liu (Peking University):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Machine learning】Revisiting Self-Supervised Visual Representation Learning

Alexander Kolesnikov (Google Brain)*:

Xiaohua Zhai (Google Brain):

Lucas Beyer (Google Brain):

【Machine learning】It’s not about the Journey; It’s about the Destination: Following Soft Paths under Question-Guidance for Visual Reasoning

Monica Haurilet (KIT)*:

Alina Roitberg (KIT):

Rainer Stiefelhagen (Karlsruhe Institute of Technology):

【Machine learning】Actively Seeking and Learning from Live Data

Damien Teney (The University of Adelaide)*:

Anton van den Hengel (University of Adelaide):

【Machine learning】Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing

Xihui Liu (The Chinese University of Hong Kong)*:

Zihao Wang (Sensetime):

Hongsheng Li (Chinese University of Hong Kong):

Jing Shao (Sensetime):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【Machine learning】Learning to sample

Oren Dovrat (Tel Aviv University)*:

Itai Lang (Tel Aviv University):

Shai Avidan (Tel Aviv University):

【Machine learning】Deep Metric Learning Beyond Binary Supervision

Sungyoun Kim (POSTECH):

Minkyo Seo (POSTECH):

Ivan Laptev (INRIA Paris): http://www.di.ens.fr/~laptev/index.html

Minsu Cho (POSTECH):

Suha Kwak (POSTECH)*:

【Machine learning】Snapshot Distillation: Teacher-Student Optimization in One Generation

Chenglin Yang (Johns Hopkins University):

Lingxi Xie (Johns Hopkins University)*:

Chi Su (Kingsoft Cloud):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Machine learning】Net Tailor: Tuning the architecture, not just the weights

Pedro Morgado (University of California, San Diego)*:

Nuno Vasconcelos (UCSD, USA): http://www.svcl.ucsd.edu/

【Machine learning】A Variational Auto-Encoder Model for Stochastic Point Processes

Nazanin Mehrasa (Simon Fraser University)*:

Akash Abdu Jyothi (Simon Fraser University):

Thibaut Durand (Simon Fraser University):

Jiawei He (Simon Fraser University):

Leonid Sigal (University of British Columbia): https://www.cs.ubc.ca/~lsigal/

Greg Mori (Simon Fraser University): http://www.cs.sfu.ca/~mori/

【Machine learning】NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction

Yuan Gao (Tencent AI Lab)*:

Jiayi Ma (Wuhan University):

Mingbo Zhao (Donghua University):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Machine learning】Spectral Metric for Dataset Complexity Assessment

Frederic Branchaud-Charron (Universite de Sherbrooke)*:

Pierre-Marc Jodoin (Universite de Sherbrooke):

Andrew Achkar (Miovision Technologies Inc., Canada):

【Machine learning】Cross-task weakly supervised learning from instructional videos

Dmitry Zhukov (Inria)*:

Jean-Baptiste Alayrac (Deep Mind):

Ramazan Gokberk Cinbis (METU):

David Fouhey (University of Michigan):

Ivan Laptev (INRIA Paris): http://www.di.ens.fr/~laptev/index.html

Josef Sivic (INRIA):

【Machine learning】Event Net: Asynchronous recursive event processing

Yusuke Sekikawa (DENSO IT Laboratory)*:

Kosuke Hara (DENSO IT Laboratory):

Hideo Saito (Keio University):

【Machine learning】Local Feature Augmentation with Cross-Modality Context

Zixin Luo (HKUST)*:

Tianwei Shen (HKUST):

Lei Zhou (HKUST):

Jiahui Zhang (Tsinghua University):

Yao Yao (The Hong Kong University of Science and Technology):

Shiwei Li (HKUST):

Tian Fang (HKUST):

Long Quan (Hong Kong University of Science and Technology): http://visgraph.cs.ust.hk/index.html

【Machine learning】AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data

Liheng Zhang (University of Central Florida):

Guo-Jun Qi (Huawei Cloud)*:

Liqiang Wang (University of Central Florida): http://www.cs.ucf.edu/~lwang/

Jiebo Luo (University of Rochester): http://www.cs.rochester.edu/u/jluo/

【Machine learning】AE^2-Nets: Autoencoder in Autoencoder Networks

Changqing Zhang (Tianjin university)*:

liu yeqing (Tianjin University ):

Huazhu Fu (Inception Institute of Artificial Intelligence):

【Machine learning】Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach

Proteek Roy (Michigan State University):

Vishnu Boddeti (Michigan State University)*:

【Machine learning】Relational Knowledge Distillation

Wonpyo Park (POSTECH)*:

Minsu Cho (POSTECH):

Yan Lu (Microsoft Research Asia):

Dongju Kim (POSTECH):

【Machine learning】Deep Spectral Clustering using Dual Autoencoder Network

Xu Yang (Xidian University):

Cheng Deng (Xidian University)*:

Feng Zheng (Southern University of Science and Technology):

Junchi Yan (Shanghai Jiao Tong University):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Machine learning】Deep Asymmetric Metric Learning via Rich Relationship Mining

Xinyi Xu (Xidian University):

Yanhua Yang (Xidian University):

Cheng Deng (Xidian University)*:

Feng Zheng (Southern University of Science and Technology):

【Machine learning】Cross-Modal Relationship Inference for Grounding Referring Expressions

Sibei Yang (The University of Hong Kong):

Guanbin Li (Sun Yat-sen University)*:

Yizhou Yu (Deepwise AI Lab): http://i.cs.hku.hk/~yzyu/

【Machine learning】Neural Sequential Phrase Grounding

Pelin Dogan (ETH Zurich)*:

Leonid Sigal (University of British Columbia): https://www.cs.ubc.ca/~lsigal/

Markus Gross (ETH Zurich):

【Machine learning】A General and Adaptive Robust Loss Function

Jonathan T Barron (Google Research)*:

【Machine learning】Soft Labels for Ordinal Regression

Raul Diaz (HP Inc)*:

Amit Marathe (HP Inc):

【Machine learning】Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

Tongtong Yuan (Beijing University of Posts and Telecommunications)*:

Jian Tang (Syracuse University):

Binghui Chen (BUPT):

Yinan Tang (Beijing University of Posts and Telecommunications):

Weihong Deng (Beijing University of Posts and Telecommunications):

【Machine learning】Density Aware Deep Metric Learning

Soumyadeep Ghosh (IIIT Delhi):

Richa Singh (IIIT-Delhi):

Mayank Vatsa (IIIT-Delhi)*:

【Machine learning】Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning

Xun Wang (Malong Technologies)*:

Xintong Han (Malong Technologies):

Weilin Huang (Malong Technologies):

Dengke Dong (Malong Technologies):

Matthew R Scott (Malong Technologies):

【Machine learning】Learning to Learn from Noisy Labeled Data

Junnan Li (National University of Singapore)*:

Wong Yongkang (National University of Singapore):

Qi Zhao (University of Minnesota):

Mohan Kankanhalli (National University of Singapore,):

【Machine learning】Label propagation for Deep Semi-supervised Learning

Ahmet Iscen (Czech Technical University)*:

Giorgos Tolias (Vision Recognition Group, Czech Technical University in Prague):

Yannis Avrithis (Inria):

Ondrej Chum (Vision Recognition Group, Czech Technical University in Prague): http://cmp.felk.cvut.cz/~chum/

【Machine learning】Ranked List Loss for Deep Metric Learning

Xinshao Wang (Queen’s University Belfast):

Yang Hua (Queen’s University Belfast)*:

Elyor Kodirov (Anyvision):

Guosheng Hu (Anyvision):

Romain Garnier (Anyvision):

Neil Robertson (Queen’s University Belfast):

【Machine learning】CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning

Chi Zhang (Nanyang Technological University)*:

Guosheng Lin (Nanyang Technological University):

Fayao Liu (University of Adelaide):

Rui Yao (China University of Mining and Technology):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

【Machine learning】Self-Supervised Convolutional Subspace Clustering Network

Junjian Zhang (Beijing University of Posts and Telecommunications):

Chun-Guang Li (Beijing University of Posts & Telecommunications)*:

Chong You (University of California, Berkeley):

Xianbiao Qi (Shenzhen Research Institute of Big Data):

Honggang Zhang (Beijing University of Posts and Telecommunications):

Jun Guo (Beijing University of Posts and Telecommunications):

Zhouchen Lin (Peking University): http://www.cis.pku.edu.cn/faculty/vision/zlin/zlin.htm

【Machine learning】Taking a Deeper Look at the Inverse Compositional Algorithm

Zhaoyang Lv (GEORGIA TECH)*:

Frank Dellaert (Georgia Tech):

James Rehg (Georgia Institute of Technology): http://www.cc.gatech.edu/~rehg/

Andreas Geiger (MPI-IS and University of Tuebingen):

【Machine learning】Learning Joint Unique-Gait and Cross-Gait Representation by Minimizing Quintuplet Loss

Kaihao Zhang (Australian National University)*:

Wenhan Luo (Tencent AI Lab):

Lin Ma (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

HONGDONG LI (Australian National University, Australia):

【Machine learning】Low-rank Tensor Completion with a New Tensor Nuclear Norm Induced by Invertible Linear Transforms

Canyi Lu (Carnegie Mellon University)*:

Xi Peng (College of Computer Science, Sichuan Univerisity):

Yunchao Wei (UIUC):

【Machine learning】Joint Representative Selection and Feature Learning: A Semi-Supervised Approach

Suchen Wang (Nanyang Technological University)*:

Jingjing Meng (State University of New York at Buffalo):

Junsong Yuan (“State University of New York at Buffalo, USA”): https://cse.buffalo.edu/~jsyuan/

Yap-Peng Tan (Nanyang Technological University, Singapore):

【Machine learning】The Domain Transform Solver

Akash Bapat (University of North Carolina at Chapel Hill)*:

Jan-Michael Frahm (UNC-Chapel Hill):

【Machine learning】Hierarchical Discrete Distribution Decomposition for Match Density Estimation

Zhichao Yin (UC Berkeley):

Trevor Darrell (UC Berkeley): http://www.eecs.berkeley.edu/~trevor/

Fisher Yu (UC Berkeley)*:

【Machine learning】Combinatorial persistency criteria for multicut and max-cut

Jan-Hendrik Lange (MPI for Informatics)*:

Bjoern Andres (University of Tübingen, Bosch Center for AI):

Paul Swoboda (MPI for Informatics):

【Machine learning】A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem

Ganzhao Yuan (Sun Yat-Sen University)*:

Li Shen (Tencent AI Lab):

WEI-SHI ZHENG (Sun Yat-sen University, China):

【Machine learning】Polynomial Representation for Persistence Diagram

Zhichao Wang (Tsinghua University)*:

Qian Li (University of Technology Sydney):

Gang Li (Deakin Univeristy, Australia):

Guandong Xu (University of Technology Sydney, Australia):

【Machine learning】Marginalized Latent Semantic Encoder for Zero-Shot Learning

Zhengming Ding (IUPUI)*:

Hongfu Liu (Brandeis University):

【Machine learning】Unsupervised Embedding Learning Using Invariant and Spreading Instance Feature

Mang YE (Hong Kong Baptist University)*:

Xu Zhang (Columbia University):

Pong Chi Yuen (Department of Computer Science, Hong Kong Baptist University):

Shih-Fu Chang (Columbia University): http://www.ee.columbia.edu/ln/dvmm/

【Machine learning】Versatile Multiple Choice Learning and Its Application to Vision Computing

Kai Tian (Fudan University):

Yi Xu (Fudan University):

Shuigeng Zhou (Fudan University)*:

Jihong Guan (Tongji University):

【Machine learning】Modularized Textual Grounding for Counterfactual Resilience

Zhiyuan Fang (Arizona State University)*:

Shu Kong (University of California, Irvine):

Charless Fowlkes (UC Irvine): http://www.ics.uci.edu/~fowlkes/

Yezhou Yang (Arizona State University): http://www.umiacs.umd.edu/~yzyang/

【Machine learning】Deeply-Supervised Knowledge Synergy

Dawei Sun (Tsinghua University):

Anbang Yao (Intel Labs China)*:

Aojun Zhou (Intel Labs China):

Hao Zhao (Intel Labs China):

【Machine learning】Semantically Aligned Bias Reducing Zero Shot Learning

Akanksha Paul (IIT Ropar)*:

Narayanan C Krishnan (IIT Ropar):

Prateek Munjal (IIT Ropar):

【Machine learning】Feature Space Perturbations Yield More Transferable Adversarial Examples

Nathan Inkawhich (Duke University)*:

Wei Wen (Duke University):

Yiran Chen (Duke University):

Hai Li (Duke University):

【Machine learning】Knowledge Distillation via Instance Relationship Graph

Yufan Liu (Institute of Automation, Chinese Academy Sciences):

Jiajiong Cao (Ant Financial):

Bing Li (National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences)*:

Chunfeng Yuan (NLPR):

Weiming Hu (Institute of Automation,Chinese Academy of Sciences): http://people.ucas.ac.cn/~huweiming

Yangxi Li (National Computer network Emergency Response technical Team/Coordination Center of China):

Yunqiang Duan (National Computer Network Emergency Response Technical Team/Coordination Center of China):

【Machine learning】La SO: Label-Set Operations networks for multi-label few-shot learning

Amit Alfassy (IBM-Research):

Leonid Karlinsky (IBM-Research)*:

Amit Aides (IBM):

Joseph Shtok (IBM-Reseach):

Sivan Harary (IBM-Research):

Rogerio Feris (IBM Research AI, MIT-IBM Watson AI Lab): http://rogerioferis.com/

Raja Giryes (Tel Aviv University):

Alex Bronstein (Technion):

【Machine learning】Few-Shot Learning with Localization in Realistic Settings

Davis Wertheimer (Cornell)*:

Bharath Hariharan (Cornell University):

【Machine learning】Ada Graph: Unifying Predictive and Continuous Domain Adaptation through Graphs

Massimiliano Mancini (Sapienza University of Rome)*:

Samuel Rota Bulò (Mapillary Research):

Barbara Caputo (IIT):

Elisa Ricci (FBK – Technologies of Vision):

【Machine learning】Large-Scale Few-Shot Learning: Knowledge Transfer with Class Hierarchy

Aoxue Li (Peking University):

Tiange Luo (Peking University):

Zhiwu Lu (Renmin University of China)*:

Tao Xiang (University of Surrey):

Liwei Wang (Peking University):

【Machine learning】Stochastic Class-based Hard Example Mining for Deep Metric Learning

Yumin Suh (Seoul National University):

Bohyung Han (Seoul National University): http://cvlab.postech.ac.kr/~bhhan/

Wonsik Kim (Samsung Electronics):

Kyoung Mu Lee (Seoul National University)*: http://cv.snu.ac.kr/kmlee/

【Machine learning】Ensemble Deep Manifold Similarity Learning using Hard Proxies

Nicolas Aziere (Oregon State University)*:

Sinisa Todorovic (Oregon State U): http://web.engr.oregonstate.edu/~sinisa/

【Machine learning】RES-PCA: A Scalable Approach to Recovering Low-rank Matrices

Chong Peng (Qingdao University)*:

Chenglizhao Chen (Qingdao University):

Zhao Kang (University of Electronic Science and Technology of China):

Jianbo Li (Qingdao University):

Qiang Cheng (University of Kentucky):

【Machine learning】Leveraging the Invariant Side of Generative Zero-Shot Learning

Jingjing Li (University of Electronic Science and Technology of China)*:

Mengmeng Jing (University of Electronic Science and Technology of China):

Ke Lu (University of Electronic Science and Technology of China):

Zhengming Ding (Indiana University-Purdue University Indianapolis):

Lei Zhu (Shandong Normal Unversity):

Zi Huang (University of Queensland):

【Machine learning】Multiple Heterogeneous Models Fitting by Multi-class Cascaded T-linkage

Luca Magri (University of Udine):

Andrea Fusiello (UNIUD)*:

【Machine learning】Joint manifold diffusion for combining predictions on decoupled observations

Kwang In Kim (UNIST)*:

Hyung Jin Chang (University of Birmingham):

【Machine learning】A Local Block Coordinate Descent Algorithm for the CSC Model

Ev Zisselman (Technion)*:

Jeremias Sulam (jhu.edu):

Michael Elad (Technion):

【Machine learning】Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Edgar Schoenfeld (University of Amsterdam)*:

Sayna Ebrahimi (UC Berkeley):

Samrath Sinha (University of Toronto):

Trevor Darrell (UC Berkeley): http://www.eecs.berkeley.edu/~trevor/

Zeynep Akata (University of Amsterdam):

【Machine learning】Learning to Compose Dynamic Tree Structures for Visual Contexts

Kaihua Tang (Nanyang Technological University)*:

Hanwang Zhang (Nanyang Technological University):

Baoyuan Wu (Tencent AI Lab):

Wenhan Luo (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Machine learning】Two Body Problem: Collaborative Visual Task Completion

Unnat Jain (UIUC)*:

Luca Weihs (Allen Institute for Artificial Intelligence):

Eric Kolve (Allen AI):

Mohammad Rastegari (Allen Institute for Artificial Intelligence):

Svetlana Lazebnik (UIUC): http://www.cs.illinois.edu/homes/slazebni/

Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence): http://homes.cs.washington.edu/~ali/index.html

Alexander Schwing (UIUC): http://www.alexander-schwing.de/

Aniruddha Kembhavi (Allen Institute for Artificial Intelligence):

【Machine learning】Learning to Learn How to Learn: Self-Adaptive Visual Navigation using Meta-Learning

Mitchell N Wortsman (Allen Institute for Artificial Intelligence):

Kiana Ehsani (University of Washington):

Mohammad Rastegari (Allen Institute for Artificial Intelligence):

Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence): http://homes.cs.washington.edu/~ali/index.html

Roozbeh Mottaghi (Allen Institute for AI)*: http://www.cs.stanford.edu/~roozbeh/

【Machine learning】Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences

Seonguk Seo (Seoul National University)*:

Paul Hongsuck Seo (POSTECH):

Bohyung Han (Seoul National University): http://cvlab.postech.ac.kr/~bhhan/

【Machine learning】Robustness via curvature regularization, and vice versa

Seyed-Mohsen Moosavi-Dezfooli (EPFL)*:

Alhussein Fawzi (Google Deepmind):

Jonathan Uesato (Deep Mind):

Pascal Frossard (EPFL):

【Machine learning】Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics

Jianjin Zhang (Tsinghua University):

Yunbo Wang (Tsinghua University):

Hongyu Zhu (Tsinghua University):

Mingsheng Long (Tsinghua University)*:

Jianmin Wang (“Tsinghua University, China”):

Philip S Yu (UIC):

【Machine learning】Dense Classification and Implanting for Few-shot Learning

Yann R Lifchitz (Safran)*:

Yannis Avrithis (Inria):

Sylvaine Picard (Safran):

Andrei Bursuc (Valeo):

【Machine learning】Class-Balanced Loss Based on Effective Number of Samples

Yin Cui (Cornell University)*:

Tsung-Yi Lin (Google Brain):

Menglin Jia (Cornell University):

Yang Song (Google): http://research.google.com/pubs/author38270.html

Serge Belongie (Cornell University): http://vision.ucsd.edu/person/serge-belongie

【Machine learning】Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning

Xi Shen (École des Ponts Paris Tech)*:

Alexei A Efros (UC Berkeley):

Mathieu Aubry (École des ponts Paris Tech): http://imagine.enpc.fr/~aubrym/

【Machine learning】Rare Event Detection using Disentangled Representation Learning

Ryuhei Hamaguchi (National Institute of Advanced Industrial Science and Technology)*:

Ken Sakurada (National Institute of Advanced Industrial Science and Technology):

Ryosuke Nakamura (National Institute of Advanced Industrial Science and Technology):

【Machine learning】Attentive Region Embedding Network for Zero-shot Learning

Guo-Sen Xie (Inception Institute of Artificial Intelligence):

Li Liu (the inception institute of artificial intelligence):

Xiao-Bo Jin (Xi’an Jiaotong-Liverpool University):

Fan Zhu (Inception Institute of Artificial Intelligence):

Zheng Zhang (The University of Queensland)*:

Jie Qin (Inception Institute of Artificial Intelligence):

Yazhou Yao (Inception Institute of Artificial Intelligence):

Ling Shao (Inception Institute of Artificial Intelligence): http://lshao.staff.shef.ac.uk/

【Machine learning】Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images

Junsik Kim (Korea Advanced Institute of Science and Technology (KAIST))*:

Tae-Hyun Oh (MIT CSAIL):

Seokju Lee (Korea Advanced Institute of Science and Technology (KAIST)):

Fei Pan (Korea Advanced Institute of Science and Technology):

In So Kweon (KAIST): http://rcv.kaist.ac.kr/

【Machine learning】Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss

Subhankar Roy (University of Trento)*:

Aliaksandr Siarohin (University of Trento):

Enver Sangineto (University of Trento):

Samuel Rota Bulo’ (Mapillary Research):

Nicu Sebe (University of Trento):

Elisa Ricci (FBK – Technologies of Vision):

【Machine learning】Efficient Parameter-free Clustering Using First Neighbor Relations

Saquib Sarfraz (Karlsruhe Institute of Technology)*:

Vivek Sharma (Karlsruhe Institute of Technology):

Rainer Stiefelhagen (Karlsruhe Institute of Technology):

【Machine learning】Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inferential Model

Tian Han (University of California, Los Angeles)*:

Erik Nijkamp (UCLA):

Xiaolin Fang (Zhejiang University):

Mitchell K Hill (UCLA Department of Statistics):

Song-Chun Zhu (UCLA): http://www.stat.ucla.edu/~sczhu/

Ying Nian Wu (University of California, Los Angeles):

【Machine learning】IMAGE DEFORMATION META-NETWORK FOR ONE-SHOT LEARNING

Zitian Chen (Fudan University):

Yanwei Fu (Fudan University)*:

Yu-Xiong Wang (Carnegie Mellon University):

Lin Ma (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Martial Hebert (Carnegie Mellon University): http://www.cs.cmu.edu/~hebert/

【Machine learning】Online high-rank matrix completion

Jicong Fan (Cornell University)*:

Madeleine Udell (Cornell University):

【Machine learning】Contact DB: Analyzing and Predicting Grasp Contact via Thermal Imaging

Samarth Brahmbhatt (Georgia Institute of Technology)*:

Cusuh Ham (Georgia Institute of Technology):

Charlie Kemp (Georgia Institute of Technology):

James Hays (Georgia Institute of Technology, USA): http://www.cs.brown.edu/~hays/

【Machine learning】Robust Subspace Clustering with Independent and Piecewise Identically Distributed Noise Modeling

Yuanman Li (University of Macau):

Jiantao Zhou (University of Macau)*:

Xianwei Zheng (Foshan University):

Jinyu Tian (University of Macau):

Yuan Yan Tang (University of Macau):

【Machine learning】Side Window Filtering

Hui Yin (Shenzhen University):

Yuanhao Gong (Shenzhen University):

Guoping Qiu (Shenzhen University)*:

【Machine learning】REPAIR: Removing Representation Bias by Dataset Resampling

Yi Li (UC San Diego)*: http://users.cecs.anu.edu.au/~yili/

Nuno Vasconcelos (UC San Diego): http://www.svcl.ucsd.edu/

【Machine learning】Label Efficient Semi-Supervised Learning via Graph Filtering

Qimai LI (The Hong Kong Poly U)*:

Xiao-Ming Wu (Poly U Hong Kong):

Han Liu (The Hong Kong Polytechnic University):

Xiaotong Zhang (The Hong Kong Polytechnic University):

Zhichao GUAN (The Hong Kong Polytechnic University):

【Machine learning】Analysis of Feature Visibility in Non-Line-of-Sight Measurements

Xiaochun Liu (University of Wisconsin – Madison)*:

Sebastian Bauer (UW Madison):

Andreas Velten (University of Wisconsin – Madison):

【Machine learning】MAGSAC: marginalizing sample consensus

Dániel Baráth (MTA SZTAKI, CMP Prague)*:

Jiri Matas (CMP CTU FEE):

Jana Noskova (CMP CTU FEE):

【Machine learning】f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning

Yongqin Xian (Max Planck Institute Informatics)*:

Saurabh Sharma (Max Planck Institute for Informatics):

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

Zeynep Akata (University of Amsterdam):

【Machine learning】Unsupervised Representation Learning by Rotation Feature Decoupling

Zeyu Feng (University of Sydney)*:

Chang Xu (University of Sydney):

Dacheng Tao (University of Sydney):

【Machine learning】A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning

Thanh-Toan Do (The University of Liverpool)*:

Toan M Tran (University of Adelaide):

Ian Reid (“University of Adelaide, Australia”): http://www.robots.ox.ac.uk/~ian/

Vijay Kumar (Xerox):

Tuan NA Hoang (Singapore University of Technology and Design):

Gustavo Carneiro (University of Adelaide): http://cs.adelaide.edu.au/~carneiro/research.html

【Machine learning】Data Representation and Learning with Graph Diffusion-Embedding Networks

Bo Jiang (Anhui University)*:

Doudou Lin (Anhui University):

Jin Tang (Anhui University):

Bin Luo (Anhui University):

【Machine learning】Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning from Radiology Reports and Label Ontology

Ke Yan (National Institutes of Health)*:

Yifan Peng (NIH):

Veit Sanfort (NIH):

Mohammadhadi Bagheri (National Institutes of Health):

Zhiyong Lu (NLM/NCBI/NIH):

Ronald Summers (National Institutes of Health, Bethesda, Maryland, United States):

【Machine learning】HAQ: Hardware-Aware Automated Quantization

Kuan Wang (MIT):

Zhijian Liu (MIT):

Yujun Lin (MIT):

Ji Lin (MIT):

Song Han (MIT)*:

【Machine learning】Meta-Learning with Differentiable Convex Optimization

Kwonjoon Lee (UC San Diego)*:

Subhransu Maji (University of Massachusetts, Amherst): http://people.cs.umass.edu/~smaji/

Avinash Ravichandran (Amazon):

Stefano Soatto (AWS Amazon ML): http://vision.ucla.edu/projects.html

【Machine learning】Tangent-Normal Adversarial Regularization for Semi-supervised Learning

Bing Yu (Peking University):

Jingfeng Wu (Peking University):

Jinwen Ma (Peking University):

Zhanxing Zhu (Peking University)*:

【Machine learning】Attention Branch Network: Learning of Attention Mechanism for Visual Explanation

Hiroshi Fukui (Chubu university)*:

Tsubasa Hirakawa (Chubu University):

Takayoshi Yamashita (Chubu University):

Hironobu Fujiyoshi (Chubu University):

【Machine learning】Task-Free Continual Learning

Rahaf Aljundi (KU Leuven)*:

Klaas Kelchtermans (KULeuven):

Tinne Tuytelaars (K.U. Leuven): http://homes.esat.kuleuven.be/~tuytelaa/

【Machine learning】Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning

Oleksiy Ostapenko (Humboldt Universität zu Berlin)*:

Tassilo Klein (SAP):

Mihai O Puscas (University of Trento):

Patrick Jähnichen (Humboldt Universität zu Berlin):

Moin Nabi (SAP):

【Machine learning】End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization

Yeonwoo Jeong (Seoul National University)*:

Yoonsung Kim (SNU Machine Learning Lab):

Hyun Oh Song (Seoul National University):

【Machine learning】Rethinking Knowledge Graph Propagation for Zero-Shot Learning

Michael C. Kampffmeyer (Ui T The Arctic University of Norway)*:

Yinbo Chen (Tsinghua University):

Xiaodan Liang (Sun Yat-sen University):

Hao Wang (Massachusetts Institute of Technology):

Yujia Zhang (Institue of Automation, Chinese Academy of Sciences):

Eric Xing (Petuum Inc. and CMU): http://www.cs.cmu.edu/~epxing/

【Machine learning】Data-Driven Neuron Allocation for Scale Aggregation Networks

Yi Li (Sense Time Research)*: http://users.cecs.anu.edu.au/~yili/

Zhanghui Kuang (Sensetime Ltd.):

Yimin Chen (sensetime):

Wei Zhang (Sense Time Research):

【Machine learning】Greedy Structure Learning of Hierarchical Compositional Models

Adam Kortylewski (Johns Hopkins University)*:

Aleksander Wieczorek (University of Basel):

Mario Wieser (University of Basel):

Clemens Blumer (University of Basel):

Andreas Morel-Forster (University of Basel):

Sonali Parbhoo (University of Basel):

Volker Roth (University of Basel):

Thomas Vetter (University of Basel):

【Machine learning】Domain-Aware Generalized Zero-Shot Learning

Yuval Atzmon (Bar-Ilan University)*:

Gal CHECHIK (Bar Ilan University):

【Machine learning】Task Agnostic Meta-Learning for Few-Shot Learning

Muhammad Abdullah Jamal (University of Central Florida)*:

Guo-Jun Qi (University of Central Florida):

【Machine learning】Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction

Hanbyul Joo (CMU)*:

Tomas Simon (CMU):

Mina Cikara (Department of Psychology, Harvard):

Yaser Sheikh (CMU): http://www.cs.cmu.edu/~yaser/

【Machine learning】Double Nuclear Norm based Low Rank Representation on Grassmann Manifolds for Clustering

Xinglin Piao (Dalian University of Technology)*:

Yongli Hu (Beijing University of Technology):

Junbin Gao (University of Sydney, Australia):

Yanfengn Sun (Beijing University of Technology):

Baocai Yin Yin (Dalian University of Technology):

【Machine learning】Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions

Zhilin Zheng (East China Normal University):

Li Sun (East China Normal University)*:

【Machine learning】Lifting Vectorial Variational Problems: A Natural Formulation based on Geometric Measure Theory and Discrete Exterior Calculus

Thomas Möllenhoff (Technical University of Munich)*:

Daniel Cremers (TUM): http://vision.in.tum.de/

【Machine learning】A Sufficient Condition for Convergences of Adam and RMSProp

Fangyu Zou (stonybrook):

Li Shen (Tencent AI Lab)*:

Zequn Jie (Tencent AI Lab):

Weizhong Zhang (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Machine learning】Guaranteed Matrix Completion under Multiple Linear Transformations

Chao Li (RIKEN)*:

Wei He (RIKEN AIP):

Longhao Yuan (Saitama Institute of Technology/RIKEN AIP):

Zhun Sun (RIKEN Center for AIP):

Qibin Zhao (RIKEN):

【Machine learning】MAP inference via Block-Coordinate Frank-Wolfe Algorithm

Paul Swoboda (MPI fuer Informatik, Saarbruecken)*:

Vladimir Kolmogorov (Institute of Science and Technology, Austria): http://pub.ist.ac.at/~vnk/

【Machine learning】Knowing When to Stop: Evaluation and Verification of Conformity to Output-size Specs

Chenglong Wang (University of Washington)*:

Rudy R Bunel (University of Oxford):

Krishnamurthy Dvijotham ():

Po-Sen Huang (Deep Mind):

Edward Grefenstette (Facebook AI Research):

Pushmeet Kohli (Deep Mind): http://research.microsoft.com/en-us/um/people/pkohli/

【Machine learning】Event Cameras, Contrast Maximization and Reward Functions: an Analysis

Timo N Stoffregen (Monash University)*:

Lindsay Kleeman (Monash University):

【Machine learning】PIEs: Pose Invariant Embeddings

Chih-Hui Ho (University of California San Diego)*:

Pedro Morgado (University of California, San Diego):

Amir Persekian (University of California, San Diego):

Nuno Vasconcelos (UC San Diego): http://www.svcl.ucsd.edu/

【Machine learning】Variational Autoencoders Recover PCA Directions

Michal Rolinek (Max Planck Institute for Intelligent Systems)*:

Dominik Zietlow (Max Planck Institute for Intelligent Systems):

Georg Martius (Max Planck Institute for Intelligent Systems):

【GAN】Feature Denoising for Improving Adversarial Robustness

Cihang Xie ( Johns Hopkins University ):

Yuxin Wu (Facebook AI Research):

Laurens van der Maaten (Facebook):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

Kaiming He (Facebook AI Research)*: http://research.microsoft.com/en-us/um/people/kahe/

【GAN】Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack

Zhezhi He (University of Central Florida)*:

Adnan Siraj Rakin (University of Central Florida):

Deliang Fan (University of Central Florida):

【GAN】Thinking Outside the Pool: Active Training Image Creation for Relative Attributes

Aron Yu (University of Texas at Austin)*:

Kristen Grauman (Facebook AI Research & UT Austin): http://www.cs.utexas.edu/~grauman/

【GAN】Generative Dual Adversarial Network for Generalized Zero-shot Learning

He Huang (University of Illinois at Chicago)*:

Changhu Wang (Byte Dance.Inc):

Philip S Yu (UIC):

Chang-Dong Wang (Sun Yat-sen University):

【GAN】So Phie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints

Amir A Sadeghian (Stanford)*:

Vineet S Kosaraju (Stanford Vision & Learning Lab):

Ali Sadeghian (University of Florida):

Noriaki Hirose (Stanford University):

Hamid Rezatofighi (Stanford University):

Silvio Savarese (Stanford University): http://cvgl.stanford.edu/silvio/

【GAN】Feedback Adversarial Learning: Spatial Feedback for Improving Generative Adversarial Networks

Jacob Huh (Carnegie Mellon University)*:

Shao-Hua Sun (University of Southern California):

Ning Zhang (UC Berkeley):

【GAN】Predicting Future Frames using Retrospective Cycle GAN

Yong-Hoon Kwon (LG Electronics)*:

Min-Gyu Park (Korea Electronics Technology Institute):

【GAN】Improving Transferability of Adversarial Examples with Input Diversity

Cihang Xie ( Johns Hopkins University ):

Yuyin Zhou (Johns Hopkins University)*:

Song Bai (University of Oxford):

Zhishuai Zhang (Johns Hopkins University):

Jianyu Wang (Baidu Research USA):

Zhou Ren (“Snap Inc.”):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【GAN】Towards Optimal Structured CNN Pruning via Generative Adversarial Learning

Shaohui Lin (Xiamen University):

Rongrong Ji (Xiamen University, China)*:

Chenqian Yan (Xiamen University):

Baochang Zhang (Beihang University):

Liujuan Cao (Xiamen University):

Qixiang Ye (University of Chinese Academy of Sciences, China): https://ucassdl.cn/content/work/paper.html

Feiyue Huang (Tencent):

David Doermann (University at Buffalo):

【GAN】OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations

Pramuditha Perera (Johns Hopkins University)*:

Ramesh Nallapati (Amazon):

Bing Xiang (Amazon):

【GAN】Mask-Guided Portrait Editing with Conditional GANs

shuyang V Gu (University of Science and Technology of China)*:

Jianmin Bao (University of Science and Technology of China):

Hao Yang (Microsoft Research Asia):

Dong Chen (Microsoft Research Asia):

Fang Wen (Microsoft Research Asia ):

Lu Yuan (Microsoft): http://research.microsoft.com/en-us/um/people/luyuan/index.htm

【GAN】Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

Hao Tang (University of Trento)*:

Dan Xu (University of Oxford):

Yan Yan (Texas State University):

Yanzhi Wang (Northeastern University):

Jason J Corso (University of Michigan):

Nicu Sebe (University of Trento):

【GAN】Label-Noise Robust Generative Adversarial Networks

Takuhiro Kaneko (The University of Tokyo)*:

Yoshitaka Ushiku (The University of Tokyo):

Tatsuya Harada (The University of Tokyo):

【GAN】Colla GAN: Collaborative GAN for Missing Image Data Imputation

Dongwook Lee (Korea Advanced Institute of Science and Technology)*:

Junyoung Kim (Korea Advanced Institute of Science and Technology):

Won-Jin Moon (Konkuk University Medical Center):

Jong Chul Ye (“Department of Bio and Brain Engineering, KAIST, Korea”):

【GAN】Spatial Fusion GAN for Image Synthesis

Fangneng Zhan (Nanyang Technological University):

Hongyuan Zhu (Institute for Infocomm, Research Agency for Science, Technology and Research (A*STAR) Singapore):

Shijian Lu (Nanyang Technological University)*:

【GAN】Sliced Wasserstein Generative Models

Jiqing Wu (ETH Zurich):

Zhiwu Huang (ETH Zurich):

Dinesh Acharya (ETH Zurich)*:

Wen Li (ETH Zurich):

Janine D Thoma (ETH Zurich):

Danda Pani Paudel (ETH Zürich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【GAN】Sphere Generative Adversarial Network Based on Geometric Moment Matching

Sung Woo Park (Chung-Ang Univ., Korea):

Junseok Kwon (Chung-Ang Univ., Korea)*:

【GAN】Balanced Self-Paced Learning for Generative Adversarial Clustering Network

Kamran Ghasedi (University of Pittsburgh)*:

Xiaoqian Wang (University of Pittsburgh):

Cheng Deng (Xidian University):

Heng Huang (University of Pittsburgh):

【GAN】A Style-Based Generator Architecture for Generative Adversarial Networks

Tero Karras (NVIDIA Research)*:

Samuli Laine (NVIDIA Research):

Timo Aila (NVIDIA Research):

【GAN】Parallel Optimal Transport GAN

Gil Avraham (Monash University)*:

Yan Zuo (Monash University):

Tom Drummond (Monash University):

【GAN】Reversible GANs for Memory-efficient Image-to-Image Translation

Tycho van der Ouderaa (University of Amsterdam)*:

Daniel E Worrall (University of Amsterdam):

【GAN】Adversarial Defense Through Network Profiling Based Path Extraction

Yuxian Qiu (Shanghai Jiao Tong University)*:

Jingwen Leng (Shanghai Jiao Tong University):

Yuhao Zhu (University of Rochester):

Cong Guo (Shanghai Jiao Tong University):

Quan Chen (Shanghai Jiao Tong University):

Chao Li (Shanghai Jiaotong University):

Minyi Guo (Shanghai Jiaotong University):

【GAN】Detection based Defense against Adversarial Examples from the Steganalysis Point of View

Jiayang Liu (University of Science and Technology of China):

Weiming Zhang (University of Science and Technology of China)*:

Yiwei Zhang (University of Science and Technology of China):

Dongdong Hou (University of Science and Technology of China):

Yujia Liu (University of Science and Technology of China):

Hongyue Zha (University of Science and Technology of China):

Nenghai Yu (University of Science and Technology of China):

【GAN】Mixture Density Generative Adversarial Networks

Hamid Eghbal-zadeh (LIT AI Lab & Johannes Kepler University, Institute of Computational Perception)*:

Werner Zellinger (Johannes Kepler University, Institute of Knowledge-Based Mathematical Systems):

Gerhard Widmer (Johannes Kepler University):

【GAN】Sketch GAN: Joint Sketch Completion and Recognition with Generative Adversarial Network

Fang Liu (Institute of Software Chinese Academy of Sciences, University of Chinese Academy of Sciences):

Xiaoming Deng (Institute of Software, Chinese Academy of Sciences):

Yukun Lai (Cardiff University):

Yong-Jin Liu (Tsinghua University):

Cuixia Ma (Institute of Software Chinese Academy of Sciences)*:

Hongan Wang (Institute of Software, Chinese Academy of Sciences):

【GAN】Com Defend: An Efficient Image Compression Model to Defend Adversarial Examples

Xiaojun Jia (Institute of Information Engineering,Chinese Academy of Sciences):

Xingxing Wei (Tsinghua University):

Xiaochun Cao (Chinese Academy of Sciences)*:

Hassan Foroosh (University of Central Florida):

【GAN】Disentangling Adversarial Robustness and Generalization

David Stutz (Max Planck Institute for Informatics)*:

Matthias Hein (University of Tübingen):

Bernt Schiele (MPI Informatics): http://www.d2.mpi-inf.mpg.de/schiele/

【GAN】Fine GAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery

Krishna Kumar Singh (University of California Davis)*:

Utkarsh Ojha (University of California, Davis):

Yong Jae Lee (University of California, Davis):

【GAN】Barrage of Random Transforms for Adversarially Robust Defense

Edward Raff (Booz Allen Hamilton)*:

Jared Sylvester (Booz Allen Hamilton):

Steven Forsyth (Nvidia):

Mark Mc Lean (Laboratory for Physical Sciences):

【GAN】3D Motion Decomposition for RGBD Future Dynamic Scene Synthesis

Xiaojuan Qi (University of Oxford)*:

Zhengzhe Liu (DJI):

Qifeng Chen (HKUST):

Jiaya Jia (Chinese University of Hong Kong): http://www.cse.cuhk.edu.hk/leojia/

【GAN】How to make a pizza: Learning a compositional layer-based GAN model

Dim P Papadopoulos (MIT)*:

Youssef Tamaazousti (MIT):

Ferda Ofli (Qatar Computing Research Institute, HBKU):

Ingmar Weber (Qatar Computing Research Institute, Qatar):

Antonio Torralba (MIT): http://web.mit.edu/torralba/www/

【GAN】Geometry-Aware Unsupervised Image-to-Image Translation

Wayne Wu (Sense Time Research)*:

Kaidi Cao (Stanford University):

Cheng Li (Sense Time Research):

Chen Qian (Sense Time):

Chen Change Loy (Nanyang Technological University): http://www.eecs.qmul.ac.uk/~ccloy/

【GAN】GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation

Xinhong Ma (National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences:

University of Chinese Academy of Sciences)*:

Tianzhu Zhang (CAS, China):

Changsheng Xu (CASIA):

【GAN】Unsupervised Primitive Discovery for Improved 3D Generative Modeling

Salman Khan (Australian National University (ANU))*:

Yulan Guo (National University of Defense Technology):

Munawar Hayat (University of Canberra):

Nick Barnes (CSIRO(Data61)):

【GAN】Beauty Glow: On-Demand Makeup Transfer Framework with Reversible Generative Network

Hung-Jen Chen (National Chiao Tung University):

Ka Ming Hui (National Chiao Tung University):

Szu Yu Wang (National Chiao Tung University):

Li-Wu Tsao (National Chiao Tung University):

Hong-Han Shuai (National Chiao Tung University)*:

Wen-Huang Cheng (EE, NCTU):

【GAN】Enhancing Triple GAN for Semi-Supervised Conditional Instance Synthesis and Classification

Si Wu (South China University of Technology)*:

Guangchang Deng (South China University of Technology):

Jichang Li (South China University of Technology):

Rui Li (City University of Hong Kong):

Zhiwen Yu (South China University of Technology):

Hau San Wong (City University of Hong Kong):

【GAN】Unsupervised Disentangling of Appearance and Geometry by Deformable Generator Network

Xianglei Xing (Harbin Engineering University)*:

Tian Han (University of California, Los Angeles):

Ruiqi Gao (UCLA):

Song-Chun Zhu (UCLA): http://www.stat.ucla.edu/~sczhu/

Ying Nian Wu (University of California, Los Angeles):

【GAN】X2CT-GAN: Reconstructing CT from Biplanar X-Rays with Generative Adversarial Networks

Xingde Ying (Zhe Jiang University ):

Heng Guo (Shanghai Jiaotong University):

Kai Ma (Tencent):

Jian Wu (Zhejiang University):

Zhengxin Weng (Shanghai Jiaotong University):

Yefeng Zheng (Tencent)*:

【GAN】Max-Sliced Wasserstein Distance and its use for GANs

Ishan Deshpande (-):

Yuan-Ting Hu (University of Illinois at Urbana-Champaign):

Ruoyu Sun (University of Illinois at Urbana-Champaign):

Ayis Pyrros (Dupagemd):

Nasir Siddiqui (Dupagemd):

Sanmi Koyejo (University of Illinois, Urbana-Champaign):

Zhizhen Zhao (University of Illinois at Urbana-Champaign):

David Forsyth (Univeristy of Illinois at Urbana-Champaign): http://luthuli.cs.uiuc.edu/~daf/

Alexander Schwing (UIUC)*: http://www.alexander-schwing.de/

【GAN】APDrawing GAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs

Ran Yi (Tsinghua University):

Yong-Jin Liu (Tsinghua University)*:

Yukun Lai (Cardiff University):

Paul Rosin (Cardiff University):

【GAN】Warp GAN: Automatic Caricature Generation

Yichun Shi (Michigan State University)*:

Debayan Deb (Michigan State University):

Anil Jain (Michigan State University):

【GAN】A Generative Adversarial Density Estimator

Ehsan M Abbasnejad (Adelaide)*:

Qinfeng Shi (University of Adelaide): https://cs.adelaide.edu.au/~javen/

Anton van den Hengel (University of Adelaide):

Lingqiao Liu (University of Adelaide):

【GAN】Detecting Overfitting of Deep Generative Networks via Latent Recovery

Ryan P Webster (Uni Caen)*:

Julien Rabin (Unicaen):

Loic Simon (GREYC/ENSICAEN):

Frederic Jurie (University of Caen):

【GAN】A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations

Saeid Asgari Taghanaki (Simon Fraser University)*:

Kumar Abhishek (Simon Fraser University ):

Shekoofeh Azizi (University of British Columbia):

Ghassan Hamarneh (Simon Fraser University):

【GAN】Adversarial Defense by Stratified Convolutional Sparse Coding

Hao Su (UCSD)*:

Ronald Yu (UCSD):

Bo Sun (Peking University):

Fangchen Liu (UCSD):

Nian-Hsuan Tsai (NTHU):

【GAN】Graphical Contrastive Losses for Scene Graph Generation

Ji Zhang (Rutgers University)*:

Kevin Shih (NVIDIA):

Andrew Tao (NVIDIA):

Bryan Catanzaro (NVIDIA):

Ahmed Elgammal (Rutgers University):

【GAN】Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images

Hao Wang (Singapore Management University)*:

Doyen Sahoo (Singapore Management University):

Chenghao Liu (Singapore Management University):

Ee-peng Lim (Singapore Management University):

Steven Hoi (SMU):

【GAN】Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks

Yunfan Liu (Institute of Automation, Chinese Academy of Sciences):

Qi Li (CASIA):

Zhenan Sun (Chinese of Academy of Sciences)*:

【GAN】Stable Generative Adversarial Training via Data Distribution Filtering

Simon Jenni (Universität Bern)*:

Paolo Favaro (University of Bern):

【GAN】Self-Supervised Generative Adversarial Networks

Ting Chen (UCLA):

Xiaohua Zhai (Google Brain):

Marvin Ritter (Google Brain):

Mario Lucic (Google Brain)*:

Neil Houlsby (Google):

【Multimodel learning】2.5D Visual Sound

Ruohan Gao (University of Texas at Austin)*:

Kristen Grauman (Facebook AI Research & UT Austin): http://www.cs.utexas.edu/~grauman/

【Multimodel learning】Mirror GAN: Learning Text-to-image Generation by Redescription

Tingting Qiao (Zhejiang University)*:

Jing Zhang (University of Technology Sydney):

Dacheng Tao (University of Sydney):

Duanqing Xu (Zhejiang University):

【Multimodel learning】Neighbourhood Watch: Referring Expression Comprehension via Language-guided Graph Attention Networks

Peng Wang (The University of Adelaide)*:

Qi Wu (University of Adelaide):

Jiewei Cao (The University of Adelaide):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Lianli Gao (The University of Electronic Science and Technology of China):

Anton van den Hengel (University of Adelaide):

【Multimodel learning】MUREL: Multimodal Relational Reasoning for Visual Question Answering

Hedi Ben-younes (Sorbonne université)*:

Remi Cadene (LIP6):

Matthieu Cord (Sorbonne University):

Nicolas Thome (CNAM, Paris):

【Multimodel learning】Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering

Chenyou Fan (Indiana University)*:

Xiaofan Zhang (JD.com):

Shu Zhang (JD.com):

Wensheng Wang (JD.com):

Chi Zhang (JD.com):

Heng Huang (University of Pittsburgh):

【Multimodel learning】Information Maximizing Visual Question Generation

Ranjay Krishna (Stanford University)*:

Michael Bernstein (Stanford University):

Li Fei-Fei (Stanford University): http://vision.stanford.edu/resources_links.html

【Multimodel learning】Learning to Detect Human-Object Interactions with Knowledge

Bingjie Xu (National University of Singapore)*:

Wong Yongkang (National University of Singapore):

Junnan Li (National University of Singapore):

Qi Zhao (University of Minnesota):

Mohan Kankanhalli (National University of Singapore,):

【Multimodel learning】Learning Words by Drawing Images

Adria Recasens (Massachusetts Institute of Technology)*:

Dídac Surís (University of Toronto):

David Bau (MIT):

David Harwath (MIT CSAIL):

James Glass (MIT):

Antonio Torralba (MIT): http://web.mit.edu/torralba/www/

【Multimodel learning】ESIR: End-to-end Scene Text Recognition via Iterative Image Rectification

Fangneng Zhan (Nanyang Technological University):

Shijian Lu (Nanyang Technological University)*:

【Multimodel learning】OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge

Kenneth Marino (Carnegie Mellon University)*:

Mohammad Rastegari (Allen Institute for Artificial Intelligence):

Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence): http://homes.cs.washington.edu/~ali/index.html

Roozbeh Mottaghi (Allen Institute for AI): http://www.cs.stanford.edu/~roozbeh/

【Multimodel learning】Semantics Disentangling for Text-to-Image Generation

Guojun Yin (University of Science and Technology of China):

Bin Liu (University of Science and Technology of China):

Lu Sheng (The Chinese University of Hong Kong)*:

Nenghai Yu (University of Science and Technology of China):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Jing Shao (Sensetime):

【Multimodel learning】Text Guided Person Image Synthesis

Xingran Zhou (Zhejiang University):

Siyu Huang (Zhejiang University)*:

Bin Li (Zhejiang University):

Yingming Li (Zhejiang University):

Jiachen Li (Nanjing University):

Zhongfei Zhang (Zhejiang University):

【Multimodel learning】Unsupervised Image Captioning

Yang Feng (University of Rochester)*:

Lin Ma (Tencent AI Lab):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

Jiebo Luo (U. Rochester): http://www.cs.rochester.edu/u/jluo/

【Multimodel learning】What’s to know? Uncertainty as a Guide to Asking Goal-oriented Questions

Ehsan M Abbasnejad (Adelaide)*:

Qi Wu (University of Adelaide):

Qinfeng Shi (University of Adelaide): https://cs.adelaide.edu.au/~javen/

Anton van den Hengel (University of Adelaide):

【Multimodel learning】Iterative Alignment Network for Continuous Sign Language Recognition

Junfu Pu (University of Science and Technology of China)*:

Wengang Zhou (University of Science and Technology of China):

Houqiang Li (University of Science and Technology of China):

【Multimodel learning】CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions

Runtao Liu (Peking University):

Chenxi Liu (Johns Hopkins University)*:

Yutong Bai (Northwestern Polytechnical University):

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Multimodel learning】Describing like Humans: on Diversity in Image Captioning

Qingzhong Wang (Department of Computer Science, City University of Hong Kong)*:

Antoni Chan (City University of Hong Kong, Hong, Kong): http://www.cs.cityu.edu.hk/~abchan/

【Multimodel learning】MSCap: Multi-Style Image Captioning with Unpaired Stylized Text

Longteng Guo ( Institute of Automation, Chinese Academy of Sciences)*:

Jing Liu (National Lab of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences):

Peng Yao (University of Science and Technology Beijing):

Jiangwei Li (Huawei):

Hanqing Lu (NLPR, Institute of Automation, CAS): http://people.ucas.ac.cn/~luhanqing

【Multimodel learning】Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence

Dahun Kim (KAIST)*:

Sanghyun Woo (KAIST):

Joon-Young Lee (Adobe Research):

In So Kweon (KAIST): http://rcv.kaist.ac.kr/

【Multimodel learning】Fast Object Class Labelling via Speech

Michael Gygli (Google)*:

Vittorio Ferrari (Google Research): http://groups.inf.ed.ac.uk/calvin/index.html

【Multimodel learning】DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-image Synthesis

Minfeng Zhu (State Key Lab of CAD&CG, Zhejiang University)*:

Pingbo Pan (University of Technology Sydney):

Wei Chen (Zhejiang University):

Yi Yang (UTS): http://www.cs.cmu.edu/~yiyang/

【Multimodel learning】Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors

Yedid Hoshen (Facebook AI Research (FAIR))*:

Ke Li (UC Berkeley):

Jitendra Malik (University of California at Berkley): http://www.cs.berkeley.edu/~malik/

【Multimodel learning】Context and Attribute Grounded Dense Captioning

Guojun Yin (University of Science and Technology of China):

Lu Sheng (The Chinese University of Hong Kong)*:

Bin Liu (University of Science and Technology of China):

Nenghai Yu (University of Science and Technology of China):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

Jing Shao (Sensetime):

【Multimodel learning】Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning

Dong-Jin Kim (KAIST)*:

Jinsoo Choi (KAIST):

Tae-Hyun Oh (MIT CSAIL):

In So Kweon (KAIST): http://rcv.kaist.ac.kr/

【Multimodel learning】Deep Modular Co-Attention Networks for Visual Question Answering

Zhou Yu (Hangzhou Dianzi University)*:

Jun Yu (HDU):

Yuhao Cui (Hangzhou Dianzi University):

Dacheng Tao (University of Sydney):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Multimodel learning】Self-critical n-step Training for Image Captioning

Junlong Gao (Peking University Shenzhen Graduate School)*:

Shiqi Wang (City U):

Shanshe Wang (Peking University):

Siwei Ma (Peking University, China):

Wen Gao (PKU): http://www.jdl.ac.cn/

【Multimodel learning】Multi-target Embodied Question Answering

Licheng Yu (University of North Carolina at Chapel Hill)*:

Xinlei Chen (Facebook AI Research):

Georgia Gkioxari (Facebook):

Mohit Bansal (University of North Carolina at Chapel Hill):

Tamara Berg (University on North carolina):

Dhruv Batra (Georgia Tech & Facebook AI Research):

【Multimodel learning】Visual question answering as reading comprehension

Hui Li (the University of Adelaide)*:

Peng Wang (Northwestern Polytechnical University):

Chunhua Shen (University of Adelaide): https://cs.adelaide.edu.au/~chhshen/

Anton van den Hengel (University of Adelaide):

【Multimodel learning】Story GAN: A Sequential Conditional GAN for Story Visualization

Yitong Li (Duke University)*:

Jianfeng Gao (Microsoft Research):

David Carlson (Duke):

Yu Cheng (Microsoft):

Zhe Gan (Microsoft):

Jingjing Liu (Microsoft):

Lawrence Carin Duke (CS):

Yelong Shen (Microsoft):

Yuexin Wu (Carnegie Mellon University):

【Multimodel learning】MFAS: Multimodal Fusion Architecture Search

Juan-Manuel Perez-Rua (Samsung)*:

Valentin Vielzeuf (Orange Labs / University of Caen):

Stephane Pateux (Orange Labs):

Moez Baccouche (Orange Labs):

Frederic Jurie (University of Caen):

【Multimodel learning】Speech2Face: Learning the Face Behind a Voice

Tali Dekel (Google)*:

Tae-Hyun Oh (MIT CSAIL):

Changil Kim (MIT CSAIL):

Michael Rubinstein (Google): http://people.csail.mit.edu/mrub/

Bill Freeman (Google): https://billf.mit.edu/

Wojciech Matusik (MIT):

Inbar Mosseri (Google):

【Multimodel learning】Audio-Visual Scene-Aware Dialog

Huda A Alamri (Georgia Institute of Technology )*:

Vincent Cartillier (Georgia Tech):

Abhishek Das (Georgia Tech):

Jue Wang (Mitsubishi Electric Research Laboratories (MERL)): http://www.juew.org/

Anoop Cherian (MERL):

Chiori Hori (Mitsubishi Electric Research Laboratories (MERL)):

Tim K Marks (Mitsubishi Electric Research Laboratories, USA):

Peter Anderson (Georgia Tech):

Stefan Lee (Georgia Institute of Technology):

Irfan Essa (Georgia Institute of Technology):

Dhruv Batra (Georgia Tech & Facebook AI Research):

Devi Parikh (Georgia Tech & Facebook AI Research): https://filebox.ece.vt.edu/~parikh/

【Multimodel learning】Listen to the Image

Di Hu (NWPU)*:

Dong Wang (Northwestern Polytechnical University):

Feiping Nie (Northwestern Polytechnical University):

Qi Wang (Northwestern Polytechnical University):

Xuelong Li (Northwestern Polytechnical University, China):

【Multimodel learning】Streamlined Dense Video Captioning

Jonghwan Mun (POSTECH)*:

Linjie Yang (Byte Dance AI Lab):

Zhou Ren (Snap Inc.):

Ning Xu (Snap):

Bohyung Han (Seoul National University): http://cvlab.postech.ac.kr/~bhhan/

【Multimodel learning】Adversarial Inference for Multi-Sentence Video Description

Jae Sung Park (UC Berkeley):

Marcus Rohrbach (Facebook AI Research):

Trevor Darrell (UC Berkeley): http://www.eecs.berkeley.edu/~trevor/

Anna Rohrbach (UC Berkeley)*:

【Multimodel learning】Unified Visual-Semantic Emebddings: Bridging Vision and Language with Structured Meaning Representations

Hao Wu (Fudan University)*:

Jiayuan Mao (Tsinghua University):

Yufeng Zhang (Fudan University):

Weiwei Sun (” Fudan University, China”):

Yuning Jiang (Bytedance):

Lei Li (Byte Dance AI Lab):

Weiying Ma (Bytedance):

【Multimodel learning】Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation

Xin Wang (University of California, Santa Barbara)*:

Qiuyuan Huang (Microsoft Research AI):

Asli Celikyilmaz (Microsoft Research AI):

Jianfeng Gao (Microsoft Research):

Dinghan Shen (Duke University):

Yuan-Fang Wang (UC Santa Barbara):

William Yang Wang (UC Santa Barbara):

Lei Zhang (Microsoft Research): http://www4.comp.polyu.edu.hk/~cslzhang/

【Multimodel learning】Dynamic Fusion with Intra- and Inter-modality Attention Flow for Visual Question Answering

gao peng (Chinese university of hong kong)*:

Hongsheng Li (Chinese University of Hong Kong):

Haoxuan You (Tsinghua University):

Zhengkai Jiang (Institute of Automation,Chinese Academy of Sciences):

Pan Lu (Tsinghua University):

Steven Hoi (SMU):

Xiaogang Wang (Chinese University of Hong Kong, Hong Kong): http://www.ee.cuhk.edu.hk/~xgwang/

【Multimodel learning】Cycle-Consistency for Robust Visual Question Answering

Meet Shah (Facebook AI Research)*:

Xinlei Chen (Facebook AI Research):

Marcus Rohrbach (Facebook AI Research):

Devi Parikh (Georgia Tech & Facebook AI Research): https://filebox.ece.vt.edu/~parikh/

【Multimodel learning】Embodied Question Answering in Photorealistic Environments with Point Cloud Perception

Erik Wijmans (Georgia Tech)*:

Samyak Datta (Georgia Tech):

Oleksandr Maksymets (Facebook AI Research):

Abhishek Das (Georgia Tech):

Georgia Gkioxari (Facebook):

Stefan Lee (Georgia Institute of Technology):

Irfan Essa (Georgia Institute of Technology):

Dhruv Batra (Georgia Tech & Facebook AI Research):

Devi Parikh (Georgia Tech & Facebook AI Research): https://filebox.ece.vt.edu/~parikh/

【Multimodel learning】Reasoning Visual Dialogs with Structural and Partial Observations

Zilong Zheng (UCLA):

Wenguan Wang (Inception Institute of Artificial Intelligence)*:

Siyuan Qi (UCLA):

Song-Chun Zhu (UCLA): http://www.stat.ucla.edu/~sczhu/

【Multimodel learning】Recursive Visual Attention in Visual Dialog

Yulei Niu (Renmin University of China):

Manli Zhang (Renmin University of China):

Jianhong Zhang (Renmin University of China):

Zhiwu Lu (Renmin University of China)*:

Ji-Rong Wen (Renmin University of China):

Hanwang Zhang (Nanyang Technological University):

【Multimodel learning】GQA: a new dataset for compositional question answering over real-world images

Drew A Hudson (Stanford University)*:

Chris Manning (Stanford):

【Multimodel learning】From Recognition to Cognition: Visual Commonsense Reasoning

Rowan Zellers (University of Washington)*:

Yonatan Bisk (University of Washington):

Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence): http://homes.cs.washington.edu/~ali/index.html

Yejin Choi (University of Washington):

【Multimodel learning】Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation

Liyiming Ke (University of Washington):

Xiujun Li (Microsoft Research)*:

Yonatan Bisk (University of Washington):

Ari Holtzman (University of Washington):

Zhe Gan (Microsoft):

Jingjing Liu (Microsoft):

Jianfeng Gao (Microsoft Research):

Yejin Choi (University of Washington):

Siddhartha Srinivasa (University of Washington):

【Multimodel learning】Show, Control and Tell: A Framework for Generating Grounded and Controllable Captions

Marcella Cornia (University of Modena and Reggio Emilia):

Lorenzo Baraldi (University of Modena and Reggio Emilia)*:

Rita Cucchiara (Universita Di Modena E Reggio Emilia): http://aimagelab.ing.unimore.it/imagelab/person.asp?idpersona=1

【Multimodel learning】Towards VQA models that can read

Amanpreet Singh (Facebook)*:

Vivek Natarajan (.):

Meet Shah (Facebook AI Research):

Yu Jiang (Facebook AI Research):

Xinlei Chen (Facebook AI Research):

Dhruv Batra (Georgia Tech & Facebook AI Research):

Devi Parikh (Georgia Tech & Facebook AI Research): https://filebox.ece.vt.edu/~parikh/

Marcus Rohrbach (Facebook AI Research):

【Multimodel learning】Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning

Junchao Zhang (Peking University):

Yuxin Peng (Peking University)*:

【Multimodel learning】Progressive Attention Memory Network for Movie Story Question Answering

Junyeong Kim (KAIST)*:

Minuk Ma (KAIST):

Kyungsu Kim (samsung research):

Sungjin Kim (SAMSUNG ELECTRONICS CO.,LTD):

Chang D. Yoo (KAIST): http://slsp.kaist.ac.kr/xe/index.php?mid=home

【Multimodel learning】Memory-Attended Recurrent Network for Video Captioning

Wenjie Pei (Tencent)*:

Jiyuan Zhang (Tencent You Tu):

Xiangrong Wang (Delft University of Technology):

Lei Ke (Tencent):

Xiaoyong Shen (Tencent):

Yu-Wing Tai (Tencent):

【Multimodel learning】Visual Query Answering by Entity-attribute Graph Matching and Reasoning

Peixi Xiong (Northwestern University)*:

HUAYI ZHAN (NORTHWESTERN UNIVERSITY):

Xin Wang (Southwest Jiaotong University):

Baivab Sinha (Sichuan Changhong Electric Co. Ltd):

Ying Wu (Northwestern University):

【Multimodel learning】Look Back and Predict Forward in Image Captioning

Yu Qin (Shanghai Jiao Tong University)*:

Jiajun Du (Shanghai Jiao Tong University):

Hongtao Lu (Shanghai Jiao Tong University):

Yonghua Zhang (Bytedance):

【Multimodel learning】Transfer Learning via Unsupervised Task Discovery for Visual Question Answering

Hyeonwoo Noh (POSTECH)*:

Taehoon Kim (DEVSISTERS):

Jonghwan Mun (POSTECH):

Bohyung Han (Seoul National University): http://cvlab.postech.ac.kr/~bhhan/

【Multimodel learning】Intention Oriented Image Captions with Guiding Objects

Yue Zheng (Tsinghua University):

Ya-Li Li (THU):

Shengjin Wang (Tsinghua University)*:

【Multimodel learning】Deep Multimodal Clustering for Unsupervised Audiovisual Learning

Di Hu (NWPU)*:

Feiping Nie (Northwestern Polytechnical University):

Xuelong Li (Northwestern Polytechnical University, China):

【Multimodel learning】Social-IQ: A Question Answering Benchmark for Open-ended Social Intelligence

Amir Zadeh (CMU LTI)*:

Michael K Chan (CMU):

Paul Pu Liang (Carnegie Mellon University):

Edmund Tong (CMU):

Louis-Philippe Morency (Carnegie Mellon University):

【Multimodel learning】Explicit Bias Discovery in Visual Question Answering Models

Varun Manjunatha (University of Maryland, College Park)*:

Nirat Saini (University of Maryland):

Larry Davis (University of Maryland): http://www.umiacs.umd.edu/~lsd/

【Multimodel learning】Image-Question-Answer Synergistic Network for Visual Dialog

Dalu Guo (University of Sydney)*:

Chang Xu (University of Sydney):

Dacheng Tao (University of Sydney):

【Multimodel learning】Adversarial Semantic Alignment for Improved Image Captions

Pierre Dognin (IBM)*:

Igor Melnyk (IBM):

Youssef Mroueh (IBM Research):

Jarret Ross (IBM):

Tom Sercu (IBM Research AI):

【Multimodel learning】Answer Them All: Toward a Universal VQA Model

Robik S Shrestha (Rochester Institute of Technology)*:

Kushal Kafle (Rochester Institute of Technology):

Christopher Kanan (Rochester Institute of Technology):

【Multimodel learning】Unsupervised Multi-modal Neural Machine Translation

Yuanhang Su (University of Southern California):

Kai Fan (Alibaba DAMO Academy)*:

Nguyen Bach (Alibaba):

C.-C. Jay Kuo (USC):

Fei Huang (Alibaba):

【Multimodel learning】Multi-task Learning of Hierarchical Vision-Language Representation

Duy Kien Nguyen (Tohoku University)*:

Takayuki Okatani (Tohoku University/RIKEN AIP):

【Multimodel learning】Connecting Touch and Vision via Cross-Modal Prediction

Yunzhu Li (MIT)*:

Jun-Yan Zhu (MIT):

Russ Tedrake (MIT):

Antonio Torralba (MIT): http://web.mit.edu/torralba/www/

【Multimodel learning】Auto-Encoding Scene Graphs for Descriptive Image Captioning

XU YANG (Nanyang Technological University)*:

Kaihua Tang (Nanyang Technological University):

Hanwang Zhang (Nanyang Technological University):

Jianfei Cai (Nanyang Technological University): http://www3.ntu.edu.sg/home/asjfcai/

【Multimodel learning】Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech

Aditya Deshpande (University of Illinois at UC)*:

Jyoti Aneja (University of Illinois, Urbana-Champaign):

Liwei Wang (Tencent AI Lab):

Alexander Schwing (UIUC): http://www.alexander-schwing.de/

David Forsyth (Univeristy of Illinois at Urbana-Champaign): http://luthuli.cs.uiuc.edu/~daf/

【Multimodel learning】Good News, Everyone! Context driven entity-aware captioning for news images

Ali Furkan Biten (Computer Vision Center)*:

Lluis Gomez (Universitat Autónoma de Barcelona):

Marçal Rusiñol (Computer Vision Center, UAB):

Dimosthenis Karatzas (Computer Vision Centre):

【Multimodel learning】Multi-level Multimodal Common Semantic Space for Image-Phrase Grounding

Hassan Akbari (Columbia University)*:

Svebor Karaman (Columbia University):

Surabhi Bhargava (Columbia University):

Brian Chen (Columbia University):

Carl Vondrick (Columbia University):

Shih-Fu Chang (Columbia University): http://www.ee.columbia.edu/ln/dvmm/

【Multimodel learning】Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning

Nayyer Aafaq (The University of Western Australia)*:

Naveed Akhtar (The University of Western Australia):

Wei Liu (University of Western Australia): http://www.ee.columbia.edu/~wliu/

Syed Zulqarnain Gilani (The University of Western Australia):

Ajmal Mian (University of Western Australia):

【Multimodel learning】Pointing Novel Objects in Image Captioning

Yehao Li (Sun Yat-Sen University):

Ting Yao (JD AI Research):

Yingwei Pan (JD AI Research)*:

Hongyang Chao (Sun Yat-sen University):

Tao Mei (AI Research of JD.com):

【Multimodel learning】Informative Object Annotations: Tell Me Something I Don’t Know

Lior Bracha (Bar Ilan University)*:

Gal CHECHIK (Bar Ilan University):

【Multimodel learning】Engaging Image Captioning via Personality

Kurt Shuster (Facebook)*:

Samuel Humeau (Facebook):

Hexiang Hu (USC):

Antoine Bordes (Facebook):

Jason Weston (FAIR):

【Multimodel learning】A Simple Baseline for Audio-Visual Scene-Aware Dialog

Idan Schwartz (Technion):

Alexander Schwing (UIUC)*: http://www.alexander-schwing.de/

Tamir Hazan (Technion):

【Transfer learning】Attending to Discriminative Certainty for Domain Adaptation

Vinod Kumar Kurmi (IIT Kanpur)*:

Shanu Kumar (IIT Kanpur):

Vinay P Namboodiri (IIT Kanpur):

【Transfer learning】Progressive Feature Alignment for Unsupervised Domain Adaptation

Chaoqi Chen (Xiamen University):

Weiping Xie (Xiamen University):

Tingyang Xu (Tencent AI Lab):

Wenbing Huang (Tencent AI Lab):

Yu Rong (Tencent AI Lab):

Xinghao Ding (Xiamen University):

Yue Huang (Xiamen University)*:

Junzhou Huang (University of Texas at Arlington):

【Transfer learning】Unsupervised Domain Adaptation by Semantic Discrepancy Minimization

Junbao Zhuo (ICT CAS):

Shuhui Wang (VIPL,ICT,Chinese academic of science)*:

Shuhao Cui ( ICT CAS):

Qingming Huang (University of Chinese Academy of Sciences):

【Transfer learning】Cr Do Co: Pixel-level Domain Transfer with Cross-Domain Consistency

Yun-Chun Chen (Academia Sinica)*:

Yen-Yu Lin (Academia Sinica):

Ming-Hsuan Yang (University of California at Merced): http://faculty.ucmerced.edu/mhyang/

Jia-Bin Huang (Virginia Tech):

【Transfer learning】Gotta Adapt ’Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild

Luan Tran (Michigan State University)*:

Kihyuk Sohn (NEC Laboratories America):

Xiang Yu (NEC Labs):

Xiaoming Liu (Michigan State University):

Manmohan Chandraker (NEC Labs America): http://cseweb.ucsd.edu/~mkchandraker/

【Transfer learning】Universal Domain Adaptation

Kaichao You (Tsinghua Univ):

Zhangjie Cao (Tsinghua University):

Mingsheng Long (Tsinghua University)*:

Jianmin Wang (“Tsinghua University, China”):

Michael Jordan (UC Berkeley): http://www.cs.berkeley.edu/~jordan/

【Transfer learning】Sequence-to-Sequence Domain Adaptation Network for Robust Text Image Recognition

Yaping Zhang (National Laboratory of Pattern Recognition, Institute of Automation, University of Chinese Academy of Sciences, Beijing, China):

Shuai Nie (National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences):

Wenju Liu (National Laboratory of Pattern Recognition, Institute of Automation, University of Chinese Academy of Sciences, Beijing, China)*:

Xing Xu (University of Electronic Science and Technology of China):

Dongxiang Zhang (University of Electronic Science and Technology of China):

Heng Tao Shen (University of Electronic Science and Technology of China (UESTC)):

【Transfer learning】Zero-Shot Task Transfer

Arghya Pal ( Indian Institute of Technology Hyderabad)*:

Vineeth N Balasubramanian (Indian Institute of Technology, Hyderabad):

【Transfer learning】Domain Generalization by Solving Jigsaw Puzzles

Fabio M. Carlucci (Huawei):

Antonio D’Innocente (Sapienza Università di Roma):

Silvia Bucci (Italian Institute of Technology):

Barbara Caputo (IIT):

Tatiana Tommasi (Italian Institute of Technology)*:

【Transfer learning】Transferrable Prototypical Networks for Unsupervised Domain Adaptation

Yingwei Pan (JD AI Research)*:

Ting Yao (JD AI Research):

Yehao Li (Sun Yat-Sen University):

Yu Wang (JD AI Research):

Chong-Wah Ngo (City University of Hong Kong):

Tao Mei (AI Research of JD.com):

【Transfer learning】Adversarial Meta-Adaptation Network for Blending-target Domain Adaptation

Ziliang Chen (Sun Yat-sen University)*:

Jingyu Zhuang (Sun Yat-sen University):

Xiaodan Liang (Sun Yat-sen University):

Liang Lin (Sun Yat-sen University): http://ss.sysu.edu.cn/~ll/index.html

【Transfer learning】Separate to Adapt: Open Set Domain Adaptation via Progressive Separation

Hong Liu (Tsinghua University):

Zhangjie Cao (Tsinghua University):

Mingsheng Long (Tsinghua University)*:

Jianmin Wang (“Tsinghua University, China”):

Qiang Yang (Hong Kong UST): http://www.cse.ust.hk/~qyang/

【Transfer learning】Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation

Jian Liang (NLPR)*:

Ran He (Institute of Automation, Chinese Academy of Sciences):

Zhenan Sun (Chinese of Academy of Sciences):

Tieniu Tan (NLPR, China): http://lab.datatang.com/1984DA173065/Default.aspx

【Transfer learning】Learning to Transfer Examples for Partial Domain Adaptation

Zhangjie Cao (Tsinghua University):

Kaichao You (Tsinghua Univ):

Mingsheng Long (Tsinghua University)*:

Jianmin Wang (“Tsinghua University, China”):

Qiang Yang (Hong Kong UST): http://www.cse.ust.hk/~qyang/

【Transfer learning】Towards Visual Feature Translation

Jie Hu (Xiamen University):

Rongrong Ji (Xiamen University, China)*:

Hong Liu (Xiamen University):

Sheng Chuan Zhang (Xiamen University):

Cheng Deng (Xidian University):

Qi Tian (Huawei Noah’s Ark Lab): http://www.cs.utsa.edu/~qitian/

【Transfer learning】Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping

Huan Fu (The University of Sydney)*:

Mingming Gong (University of Pittsburgh):

Chaohui Wang (Laboratoire d’Informatique Gaspard Monge, Université Paris-Est):

Kayhan Batmanghelich (University of Pittsburgh / Carnegie Mellon University):

Kun Zhang (Carnegie Mellon University):

Dacheng Tao (University of Sydney):

【Transfer learning】DLOW: Domain Flow for Adaptation and Generalization

Wen Li (ETH Zurich)*:

RUI GONG (ETH Zurich):

Yuhua Chen (ETH Zurich):

Luc Van Gool (ETH Zurich): http://www.vision.ee.ethz.ch/

【Transfer learning】STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing

Ming Liu (Harbin Institute of Technology, China):

Yukang Ding (Baidu Research):

Min Xia (Harbin Institute of Technology, China):

Xiao Liu (Baidu):

Errui Ding (Baidu Inc.):

Wangmeng Zuo (Harbin Institute of Technology, China)*:

Shilei Wen (Baidu Research):

【Transfer learning】Semi-supervised Transfer Learning for Image Rain Removal

Wei Wei (Northwestern University)*:

Deyu Meng (Xi’an Jiaotong University):

Qian Zhao (Xi’an Jiaotong University ):

Zongben Xu (Xi’an Jiaotong University):

Ying Wu (Northwestern University):

【Transfer learning】d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding

Xiang Xu (University of Houston):

Xiong Zhou (amazon):

Ragav Venkatesan (Amazon)*:

Orchid Majumder (Amazon):

Guru Swaminathan (Amazon):

【Transfer learning】Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation

Yawei Luo (University of Technology Sydney)*:

Liang Zheng (Australian National University):

Tao Guan (Huazhong University of Science and Technology):

Junqing Yu (Huazhong University of Science & Technology):

Yi Yang (University of Technology, Sydney): http://www.cs.cmu.edu/~yiyang/

【Transfer learning】ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

Tuan-Hung VU (Valeo.ai)*:

Himalaya Jain (Valeo.ai):

Maxime Bucher (Valeo.ai):

Matthieu Cord (Sorbonne University):

Patrick Pérez (Valeo.ai):

【Transfer learning】Do Better Image Net Models Transfer Better?

Simon Kornblith (Google)*:

Jon Shlens (Google):

Quoc Le (Google Brain):

【Transfer learning】Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach

Minyoung Kim (Seoul Tech, Rutgers University)*:

Pritish Sahu (Rutgers University):

Behnam Gholami (Rutgers University):

Vladimir Pavlovic (Rutgers University):

【Transfer learning】Spot Tune: Transfer Learning through Adaptive Fine-tuning

Yunhui Guo (University of California, San Diego)*:

Honghui Shi (IBM | UIUC):

Abhishek Kumar (Google):

Kristen Grauman (Facebook AI Research & UT Austin): http://www.cs.utexas.edu/~grauman/

Tajana Rosing (University of California, San Diego):

Rogerio Feris (IBM Research AI, MIT-IBM Watson AI Lab): http://rogerioferis.com/

【Transfer learning】Contrastive Adaptation Network for Unsupervised Domain Adaptation

Guoliang Kang (UTS)*:

Lu Jiang (Google):

Yi Yang (UTS): http://www.cs.cmu.edu/~yiyang/

Alexander Hauptmann (Carnegie Mellon University):

【Transfer learning】Domain-Symmetric Networks for Adversarial Domain Adaptation

Yabin Zhang (South China University of Technology):

Hui Tang (South China University of Technology):

Kui Jia (South China University of Technology)*:

Mingkui Tan (South China University of Technology):

【Transfer learning】Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration

Shuhan Tan (Sun-Yat-Sen University, China)*:

Jiening Jiao (Sun Yat-sen University, China ):

WEI-SHI ZHENG (Sun Yat-sen University, China):

【Transfer learning】Unsupervised Domain Adaptation for To F Data Denoising with Adversarial Learning

Gianluca Agresti (University of Padova)*:

Henrik Schaefer (Sony Europe Ltd.):

Piergiorgio Sartor (Sony Europe Limited):

Pietro Zanuttigh (University of Padova):

【Transfer learning】Variational Information Distillation for Knowledge Transfer

Sungsoo Ahn (KAIST)*:

Shell Hu (ENPS):

Andreas Damianou (Amazon):

Neil Lawrence (Amazon):

Zhenwen Dai (Amazon):

【Transfer learning】Min-Max Statistical Alignment for Transfer Learning

Samitha Herath (The Australian National University)*:

Basura Fernando (Agency for Science, Technology and Research, A*STAR, Singapore):

Mehrtash Harandi (Monash University):

Richard Nock (Data61-CSIRO):

【Transfer learning】Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

Chen-Yu Lee (Apple)*:

Tanmay Batra (Apple):

Mohammad Haris Baig (Apple):

Daniel Ulbricht (apple):

【Transfer learning】Characterizing and Avoiding Negative Transfer

Zirui Wang (Carnegie Mellon University)*:

Zihang Dai (Carnegie Mellon University):

Barnabas Poczos ( Carnegie Mellon University):

Jaime Carbonell (Carnegie Mellon University):

【Transfer learning】Cham Net: Towards Efficient Network Design through Platform-Aware Model Adaptation

Xiaoliang Dai (Princeton University)*:

Peizhao Zhang (Facebook):

Bichen Wu (UC Berkeley):

Hongxu Yin (Princeton University):

Fei Sun (Facebook):

Yanghan Wang (Facebook):

Marat Dukhan (Facebook):

Yunqing Hu (Facebook):

Yiming Wu (Facebook):

Yangqing Jia (Facebook): http://www.eecs.berkeley.edu/~jiayq/

Peter Vajda (Facebook):

Matt Uyttendaele (Facebook):

Niraj K Jha (Princeton University):

【Transfer learning】Exploring Object Relation in Mean Teacher for Cross-Domain Detection

Qi Cai (University of Science and Technology of China):

Yingwei Pan (JD AI Research)*:

Chong-Wah Ngo (City University of Hong Kong):

Xinmei Tian (USTC):

Lingyu Duan (Peking University):

Ting Yao (JD AI Research):

【Transfer learning】Deep Transfer Learning for Multiple Class Novelty Detection

Pramuditha Perera (Johns Hopkins University)*:

Vishal Patel (Johns Hopkins University):

【Transfer learning】Deep Defocus Map Estimation using Domain Adaptation

Junyong Lee (POSTECH):

Sungkil Lee (Sungkyunkwan University):

Sunghyun Cho (DGIST):

Seungyong Lee (POSTECH)*: http://cg.postech.ac.kr/leesy/

【Transfer learning】Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning

Kshitij Dwivedi (Singapore University of Technology and Design)*:

Gemma Roig (MIT):

【Reinforcement learning】Enhanced Bayesian Compression via Deep Reinforcement Learning

Xin Yuan (Tsinghua University):

Liangliang Ren (Tsinghua University):

Jiwen Lu (Tsinghua University)*:

Jie Zhou (Tsinghua University): https://www.tsinghua.edu.cn/publish/auen/1713/2011/20110506105532098625469/20110506105532098625469_.html

【Reinforcement learning】IRLAS: Inverse Reinforcement Learning for Architecture Search

Minghao Guo (Sensetime)*:

Zhao Zhong (CASIA):

Wei Wu (Sense Time Group Limited):

Dahua Lin (The Chinese University of Hong Kong): http://dahua.me/

Junjie Yan (Sensetime Group Limited): http://www.cbsr.ia.ac.cn/users/jjyan/main.htm

【Attack learning】Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples

Zihao Liu (Florida International University)*:

Tao Liu (Florida International University):

Qi Liu (Florida International University ):

Nuo Xu (Florida International University):

Xue Lin (Northeastern University):

Yanzhi Wang (Northeastern University):

Wujie Wen (Florida International University):

【Attack learning】Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables

Yan Xu (UESTC):

Baoyuan Wu (Tencent AI Lab)*:

Fumin Shen (UESTC):

Yanbo Fan (Tencent AI Lab):

Yong Zhang (Tencent AI Lab):

Heng Tao Shen (University of Electronic Science and Technology of China (UESTC)):

Wei Liu (Tencent): http://www.ee.columbia.edu/~wliu/

【Attack learning】Adversarial Attacks Beyond the Image Space

xiaohui zeng (toronto):

Chenxi Liu (Johns Hopkins University)*:

Yu-Siang Wang (National Taiwan University):

Weichao Qiu (Johns Hopkins University):

Lingxi Xie (Johns Hopkins University):

Yu-Wing Tai (Tencent):

Chi-Keung Tang (Hong Kong University of Science and Technology): http://www.cs.ust.hk/~cktang/bio-sketch-review.htm

Alan Yuille (Johns Hopkins University): http://www.stat.ucla.edu/~yuille/

【Attack learning】Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks

Yinpeng Dong (Tsinghua University)*:

Tianyu Pang (Tsinghua University):

Hang Su (Tsinghua Univiersity):

Jun Zhu (Tsinghua University):

【Attack learning】Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses

Jérôme Rony (ÉTS Montréal)*:

Luiz Gustavo Hafemann (ÉTS Montréal):

Luis Eduardo Oliveira (UFPR):

Ismail Ben Ayed (ETS Montreal):

Robert Sabourin (Canada):

Eric Granger (ETS Montreal ):

【Attack learning】What does it mean to learn in deep networks? And, how does one detect adversarial attacks?

Ciprian Corneanu (Universitat de Barcelona)*:

Aleix M Martinez (OSU):

Sergio Escalera (Computer Vision Center (UAB) & University of Barcelona,): http://sergioescalera.com/

Meysam Madadi (CVC):

【Attack learning】Strike

Michael A Alcorn (Auburn University):

Qi Li (Auburn University):

Zhitao Gong (Auburn University):

Chengfei Wang (Auburn University):

Long T Mai (Adobe Research):

Wei-Shinn Ku (Auburn University):

Anh Nguyen (Auburn University)*:

【Attack learning】Shield Nets: Defending Against Adversarial Attacks using Policy Gradient Reinforcement Learning

Rajkumar Theagarajan (University of California, Riverside)*:

Ming Chen ( Lawrence Berkeley National Laboratory):

BIR BHANU (UC RIVERSIDE, USA.):

Jing Zhang (KLA-Tencor):

【Attack learning】Curls & Whey: Boosting Black-Box Adversarial Attacks

Yucheng Shi (Tianjin University):

Siyu Wang (Tianjin University):

Yahong Han (Tianjin University)*:

【Attack learning】Catastrophic Child’s Play: Easy to Perform, Hard to Defend Adversarial Attacks

Chih-Hui Ho (University of California San Diego)*:

Erik Sandström (Lund University):

Brandon Leung (University of California, San Diego):

Yen Chang (University of California, San Diego):

Nuno Vasconcelos (UC San Diego): http://www.svcl.ucsd.edu/

【Attack learning】Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search

Abhimanyu Dubey (Massachusetts Institute of Technology)*:

Laurens van der Maaten (Facebook):

Zeki Yalniz (Facebook):

Yixuan Li (Facebook Research):

Dhruv Mahajan (Facebook):

【Attack learning】Multi-adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection

Rui Shao (Department of Computer Science, Hong Kong Baptist University)*:

Xiangyuan Lan (Department of Computer Science, Hong Kong Baptist University):

Jiawei Li (Hong Kong Baptist University):

Pong Chi Yuen (Department of Computer Science, Hong Kong Baptist University):

【Attack learning】Defending against adversarial attacks by randomized diversification

Olga Taran (Geneva University)*:

Shideh Rezaeifar (Geneva University):

Taras Holotyak (Geneva University):

Slava Voloshynovskiy (CUI, University of Geneva):

【Attack learning】Adv-GAN: Generator, Discriminator, and Adversarial Attacker

Xuanqing Liu (UCLA Department of Computer Science):

Cho-Jui Hsieh (UCLA, Google)*:

【Attack learning】Trust Region Based Adversarial Attack on Neural Networks

Zhewei Yao (University of California, Berkeley):

Amir Gholami (UC Berkeley)*:

Peng Xu (Amazon):

Kurt Keutzer (EECS, UC Berkeley):

Michael Mahoney (“University of California, Berkeley”):

【Attack learning】Additive Adversarial Learning for Unbiased Authentication

Jian Liang (Cloud and Smart Industries Group, Tencent, Beijing)*:

Yuren Cao (Cloud and Smart Industries Group, Tencent, Guangzhou):

Chenbin Zhang (University of Electronic Science and Technology of China):

Shiyu Chang (IBM Research):

Kun Bai (Tencent Inc):

Zenglin Xu (University of Electronic Science and Technology of China):

【Attack learning】Robustness of 3D Deep Learning in an Adversarial Setting

Matthew R Wicker (University of Oxford)*:

Marta Kwiatkowska (University of Oxford):

【Graph NN】Exploiting Edge Features in Graph Neural Networks

Liyu Gong (University of Kentucky)*:

Qiang Cheng (University of Kentucky):

【Graph NN】Explainability Methods for Graph Convolutional Neural Networks

Phillip Pope (HRL Laboratories, LLC):

Soheil Kolouri (HRL Laboratories LLC)*:

Mohammad Rostami (HRL Laboratories, LLC):

Charles Martin (HRL Laboratories, LLC):

Heiko Hoffmann (HRL):

【Graph NN】Semi-supervised Learning with Graph Learning-Convolutional Networks

Bo Jiang (Anhui University)*:

Ziyan Zhang (Anhui University):

Doudou Lin (Anhui University):

Jin Tang (Anhui University):

Bin Luo (Anhui University):