2016 ECCV

下面是2016 ECCV文章的主题标签,文章列表来源于http://www.eccv2016.org/main-conference/
Topic: Scene parsing; Object segmentation; Image segmentation; Video segmentation; Boundary detection; Contour analysis; Object tracking; Action recognition; Crowd analysis; Human detection; Human parsing; Face recognition; Face parsing; Object recognition; Object detection; Saliency detection; Scene recognition; Text recognition; Image retrieval; 3D modeling; Feature matching; Pose estimation; Stereo matching;Optical flow;Region matching; Image editing; Computational photography; Texture analysis; Data clustering; Space reduction; Machine learning; Deep learning;
【Scene parsing】S-1A-07.   Segmentation from Natural Language Expressions

PDF: http://www.eccv2016.org/files/posters/S-1A-07.pdf

Ronghang Hu, UC Berkeley:

Marcus Rohrbach, UC Berkeley:

Trevor Darrell: http://www.eecs.berkeley.edu/~trevor/

【Scene parsing】S-1A-08.   Semantic Object Parsing with Graph LSTM

PDF: http://www.eccv2016.org/files/posters/S-1A-08.pdf

Xiaodan Liang, Sun Yat-sen University:

Xiaohui Shen, Adobe:

Jiashi Feng, NUS:

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

Shuicheng Yan, NUS: http://www.lv-nus.org/index.html

【Scene parsing】P-1A-23.   Region-based semantic segmentation with end-to-end training

PDF: http://www.eccv2016.org/files/posters/P-1A-23.pdf

Holger Caesar, University of Edinburgh:

Jasper Uijlings, Univ. of Edinburgh:

Vittorio Ferrari: http://groups.inf.ed.ac.uk/calvin/index.html

【Scene parsing】O-1B-03.   Improving Multi-label Learning with Missing Labels by Structured Semantic Correlations

PDF: http://www.eccv2016.org/files/posters/O-1B-03.pdf

Hao Yang, NTU:

Joey Tianyi Zhou, IHPC:

Jianfei Cai, NTU: http://www3.ntu.edu.sg/home/asjfcai/

【Scene parsing】O-1B-04.   Visual Relationship Detection with Language Priors

PDF: http://www.eccv2016.org/files/posters/O-1B-04.pdf

Cewu Lu, Stanford University:

Ranjay Krishna, Stanford University:

Michael Bernstein, Stanford University:

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

【Scene parsing】S-1B-07.   Facilitating and Exploring Planar Homogeneous Texture for Indoor Scene Understanding

PDF: http://www.eccv2016.org/files/posters/S-1B-07.pdf

Shahzor Ahmad, National University of Singapo:

Loong-Fah Cheong, National University of Singapore:

【Scene parsing】P-1B-18.   What’s the Point: Semantic Segmentation with Point Supervision

PDF: http://www.eccv2016.org/files/posters/P-1B-18.pdf

Amy Bearman, Stanford University:

Olga Russakovsky, Stanford University:

Vittorio Ferrari,: http://groups.inf.ed.ac.uk/calvin/index.html

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

【Scene parsing】P-1B-38.   LSTM-CF: Unifying Context Modeling and Fusion with LSTMs for RGB-D Scene Labeling

PDF: http://www.eccv2016.org/files/posters/P-1B-38.pdf

Zhen Li, The University of Hong Kong:

Yukang Gan, Sun Yat-sen University:

Xiaodan Liang, Sun Yat-sen University:

Yizhou Yu, The University of Hong Kong: http://i.cs.hku.hk/~yzyu/

Hui Cheng,:

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

【Scene parsing】P-2A-42.   Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation

PDF: http://www.eccv2016.org/files/posters/P-2A-42.pdf

Golnaz Ghiasi, University of California, Irvine:

Charless Fowlkes: http://www.ics.uci.edu/~fowlkes/

【Scene parsing】P-2B-11.   A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning.

PDF: http://www.eccv2016.org/files/posters/P-2B-11.pdf

Terrell Mundhenk, Lawrence Livermore National L.:

Wesam Sakla, LLNL:

Goran Konjevod, LLNL:

Kofi Boakye, LLNL:

【Scene parsing】P-2B-35.   Top-down Learning for Structured Labeling with Convolutional Pseudoprior

PDF: http://www.eccv2016.org/files/posters/P-2B-35.pdf

Saining Xie, UCSD:

Xun Huang,:

Zhuowen Tu: http://pages.ucsd.edu/~ztu/

【Scene parsing】P-2B-37.   Joint learning of Semantic and Latent Attributes

PDF: http://www.eccv2016.org/files/posters/P-2B-37.pdf

Peixi Peng, Peking University:

Yonghong Tian, Peking University:

Tao Xiang, Queen Mary University of London:

Yaowei Wang, Beijing Institute of Technology:

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

【Scene parsing】P-2B-40.   Weakly-Supervised Semantic Segmentation using Motion Cues

PDF: http://www.eccv2016.org/files/posters/P-2B-40.pdf

Pavel Tokmakov, INRIA Grenoble Rhône-Alpes:

Karteek Alahari, Inria:

Cordelia Schmid: http://lear.inrialpes.fr/~schmid/

【Scene parsing】P-3A-15.   Semantic Co-segmentation in Videos

PDF: http://www.eccv2016.org/files/posters/P-3A-15.pdf

Yi-Hsuan Tsai, UC Merced:

Guangyu Zhong, Dalian Universityof Technolog:

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Scene parsing】P-3A-40.   Recurrent Temporal Deep Field for Semantic Video Labeling

PDF: http://www.eccv2016.org/files/posters/P-3A-40.pdf

Peng Lei, Oregon State University:

Sinisa Todorovic, Oregon State University: http://web.engr.oregonstate.edu/~sinisa/

【Scene parsing】P-3A-45. SPICE: Semantic Propositional Image Caption Evaluati

Peter Anderson, Australian National University:

Basura Fernando, ANU:

Mark Johnson, Macquarie University:

Stephen Gould, Australian National University: http://users.cecs.anu.edu.au/~sgould/index.html

【Scene parsing】P-3B-14.   Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs

PDF: http://www.eccv2016.org/files/posters/P-3B-14.pdf

Siddhartha Chandra, INRIA:

Iasonas Kokkinos, INRIA: http://cvn.ecp.fr/personnel/iasonas/index.html

【Scene parsing】P-3B-29.   Figure Seer: Parsing Result-Figures in Research Papers

PDF: http://www.eccv2016.org/files/posters/P-3B-29.pdf

Noah Siegel,:

Zachary Horvitz,:

Roie Levin,:

Santosh Kumar Divvala, Allen Institute for Artificial Intelligence:

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

【Scene parsing】P-3B-46.   Augmented Feedback in Semantic Segmentation under Image Level Supervision

PDF: http://www.eccv2016.org/files/posters/P-3B-46.pdf

Xiaojuan Qi, CUHK:

Zhengzhe liu,:

Jianping Shi, Sense Time:

Hengshuang Zhao,:

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

【Scene parsing】P-3C-23.   Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation

PDF: http://www.eccv2016.org/files/posters/P-3C-23.pdf

Fatemehsadat Saleh, The Australian National University/CSIRO:

Mohammad Sadegh Aliakbarian, National ICT Australia:

Mathieu Salzmann, EPFL:

Lars Petersson, NICTA:

Stephen Gould, Australian National University: http://users.cecs.anu.edu.au/~sgould/index.html

Jose M. Alvarez, Data61 / CSIRO:

【Scene parsing】P-4A-19.   Learning Dynamic Hierarchical Models for Anytime Scene Labeling

PDF: http://www.eccv2016.org/files/posters/P-4A-19.pdf

Buyu Liu, NICTA:

Xuming He, NICTA: http://users.cecs.anu.edu.au/~hexm/

【Scene parsing】P-4B-14.   Learning Common and Specific Features for RGB-D Semantic Segmentation with Deconvolutional Networks

PDF: http://www.eccv2016.org/files/posters/P-4B-14.pdf

Jinghua Wang, NTU:

Zhenhua Wang, NTU, ROSE Lab:

Dacheng Tao, University of Technology, Sydney:

Simon See,:

Gang Wang:

【Scene parsing】P-4B-45. Learning Semantic Deformation Flows with 3D Convolutional Networks

Ersin Yumer, Adobe Research:

Niloy Mitra, University College London:

【Object segmentation】S-1A-05.   Learning to Refine Object Segments

PDF: http://www.eccv2016.org/files/posters/S-1A-05.pdf

Pedro Pinheiro, EPFL:

Tsung-Yi Lin, Cornell:

Ronan Collobert, Facebook:

Piotr Dollar, Facebook: http://vision.ucsd.edu/~pdollar/

【Object segmentation】S-1A-06.   Deep Automatic Portrait Matting

PDF: http://www.eccv2016.org/files/posters/S-1A-06.pdf

Xiaoyong Shen, CUHK:

Xin Tao, CUHK:

Hongyun Gao, CUHK:

Chao Zhou,:

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

【Object segmentation】P-1A-19.   Foreground Segmentation via Dynamic Tree-Structured Sparse RPCA

PDF: http://www.eccv2016.org/files/posters/P-1A-19.pdf

Salehe Erfanian Ebadi, Queen Mary University of London:

Ebroul Izquierdo, Queen Mary University of London:

【Object segmentation】P-1B-17.   A Cluster Sampling Method for Image Matting via Sparse Coding

PDF: http://www.eccv2016.org/files/posters/P-1B-17.pdf

Xiaoxue Feng, Beihang University:

Xiaohui Liang, State Key Lab. of Virtual Reality Technology and Systems:

Zili Zhang, State Key Lab. of Virtual Reality Technology and Systems:

【Object segmentation】P-1B-43.   Natural Image Matting using Deep Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-1B-43.pdf

Donghyeon Cho, KAIST:

Yu-Wing Tai, Korea Advanced Institute of Science and Technology:

In So Kweon, KAIST: http://rcv.kaist.ac.kr/

【Object segmentation】P-1B-46.   Amodal Instance Segmentation

PDF: http://www.eccv2016.org/files/posters/P-1B-46.pdf

Ke Li, UC Berkeley:

Jitendra Malik, UC Berkeley: http://www.cs.berkeley.edu/~malik/

【Object segmentation】P-2B-28.   A Multi-Scale CNN for Affordance Segmentation in RGB Images

PDF: http://www.eccv2016.org/files/posters/P-2B-28.pdf

Anirban Roy, Oregon State University:

Sinisa Todorovic, Oregon State University: http://web.engr.oregonstate.edu/~sinisa/

【Object segmentation】P-3C-13.   Real-Time Facial Segmentation and Performance Capture from RGB Input

PDF: http://www.eccv2016.org/files/posters/P-3C-13.pdf

Shunsuke Saito, USC:

Tianye Li, USC:

Hao Li, USC:

【Object segmentation】P-3C-24.   It’s Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos

PDF: http://www.eccv2016.org/files/posters/P-3C-24.pdf

Pia Bideau, Umass Amherst:

Erik Miller:

【Object segmentation】P-4A-24.   Image Co-segmentation using Maximum Common Subgraph Matching and Region Co-growing

PDF: http://www.eccv2016.org/files/posters/P-4A-24.pdf

Avik Hati, IIT Bombay:

Subhasis Chaudhuri, IIT Bombay:

Rajbabu Velmurugan, IIT Bombay:

【Object segmentation】P-4B-46.   Recurrent Instance Segmentation

PDF: http://www.eccv2016.org/files/posters/P-4B-46.pdf

Bernardino Romera-Paredes, University of Oxford:

Philip Torr, Oxford University: http://www.robots.ox.ac.uk/~tvg/

【Image segmentation】S-1A-09.   SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation

PDF: http://www.eccv2016.org/files/posters/S-1A-09.pdf

Ting Liu, University of Utah:

Miaomiao Zhang, MIT:

Mehran Javanmardi, University of Utah:

Nisha Ramesh, University of Utah:

Tolga Tasdizen, University of Utah: http://www.sci.utah.edu/~tolga/

【Image segmentation】P-1A-36.   Superpixel Convolutional Networks using Bilateral Inceptions

PDF: http://www.eccv2016.org/files/posters/P-1A-36.pdf

Raghudeep Gadde, Ecole des Ponts Paris Tech:

Varun Jampani, MPI-IS:

Martin Kiefel, MPI for Intelligent Systems:

Daniel Kappler, MPI Intelligent Systems:

Peter Gehler:

【Image segmentation】P-2B-16.   HFS: Hierarchical Feature Selection for Efficient Image Segmentation

PDF: http://www.eccv2016.org/files/posters/P-2B-16.pdf

Ming-Ming Cheng, Nankai University:

Yun Liu, Nankai University:

Qibin Hou, Nankai University:

Jiawang Bian, Nankai University:

Philip Torr, Oxford University: http://www.robots.ox.ac.uk/~tvg/

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

Zhuowen Tu: http://pages.ucsd.edu/~ztu/

【Image segmentation】P-3A-11.   Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation

PDF: http://www.eccv2016.org/files/posters/P-3A-11.pdf

Alexander Kolesnikov, IST Austria:

Christoph Lampert, IST Austria:

【Image segmentation】P-3C-15.   Interactive Image Segmentation Using Constrained Dominant Sets

PDF: http://www.eccv2016.org/files/posters/P-3C-15.pdf

Eyasu Zemene, Ca’Foscari University:

Marcello Pelillo, University of Venice:

【Image segmentation】P-4A-35.   Light Field Segmentation Using a Ray-Based Graph Structure

PDF: http://www.eccv2016.org/files/posters/P-4A-35.pdf

Matthieu Hog, Technicolor R&I:

Neus Sabater, Technicolor R&I:

Christine Guillemot, INRIA:

【Video segmentation】P-4A-16.   Streaming Video Segmentation via Short-Term Hierarchical Segmentation and Frame-by-Frame Markov Random Field Optimization

PDF: http://www.eccv2016.org/files/posters/P-4A-16.pdf

Won-Dong Jang, Korea University:

Chang-Su Kim, Korea University:

【Boundary detection】P-1A-33.   DOC: Deep OCclusion Estimation From a Single Image

PDF: http://www.eccv2016.org/files/posters/P-1A-33.pdf

Peng Wang, UCLA:

Alan Yuille, UCLA: http://www.stat.ucla.edu/~yuille/

【Boundary detection】P-1A-35.   Convolutional Oriented Boundaries

PDF: http://www.eccv2016.org/files/posters/P-1A-35.pdf

Kevis-Kokitsi Maninis, ETH Zürich:

Jordi Pont-Tuset, ETHZ:

Pablo Arbelaez, Universidad de los Andes, Colombia: http://www.cs.berkeley.edu/~arbelaez/

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

【Contour analysis】P-1A-14.   Eigen Appearance Maps of Dynamic Shapes

PDF: http://www.eccv2016.org/files/posters/P-1A-14.pdf

Adnane Boukhayma, Inria:

vagia Tsiminaki, Inria:

Jean-Sebastien Franco, LJK, Université Grenoble Alpes, Inria:

Edmond Boyer, Inria:

【Contour analysis】P-1A-21.   Efficient Multi-view Surface Refinement with Adaptive Resolution Control

PDF: http://www.eccv2016.org/files/posters/P-1A-21.pdf

Shiwei Li, HKUST:

Sing Yu Siu, HKUST:

Tian Fang, HKUST:

Long Quan, The Hong Kong University of Science and Technology, Hong Kong: http://visgraph.cs.ust.hk/index.html

【Contour analysis】S-3B-06.   Capturing Dynamic Textured Surfaces of Moving Targets

PDF: http://www.eccv2016.org/files/posters/S-3B-06.pdf

Ruizhe Wang, USC:

Lingyu Wei, USC:

Etienne Vouga, UT Austin:

Qixing Huang, TTI-Chicago:

Duygu Ceylan, Adobe Research:

Gerard Medioni, University of Southern California:

Hao Li, USC:

【Contour analysis】S-3B-08.   Heat Diffusion Long-Short Term Memory Learning for 3D Shape Analysis

PDF: http://www.eccv2016.org/files/posters/S-3B-08.pdf

Fan Zhu, NYUAD:

Jin Xie, NYUAD:

Yi Fang, New York University Abu Dhabi:

【Contour analysis】P-4A-43.   Surf Cut: Free-Boundary Surface Extraction

PDF: http://www.eccv2016.org/files/posters/P-4A-43.pdf

Marei Algarni, KAUST University:

Ganesh Sundaramoorthi, KAUST:

【Contour analysis】S-4B-05.   General Automatic Human Shape and Motion Capture Using Volumetric Contour Cues

PDF: http://www.eccv2016.org/files/posters/S-4B-05.pdf

Helge Rhodin, MPI for informatics:

Nadia Robertini, Max-Planck-Institute for informatics:

Dan Casas, MPI:

Christian Richardt, Intel VCI:

Hans-Peter Seidel,:

Christian Theobalt, MPI Informatics:

【Contour analysis】P-4B-41.   Deep learning 3D shape surfaces using geometry images

PDF: http://www.eccv2016.org/files/posters/P-4B-41.pdf

Ayan Sinha, Purdue University:

Jing Bai, Purdue University:

Karthik Ramani, Purdue University:

【Object tracking】P-1A-10.   Fundamental Matrices from Moving Objects Using Line Motion Barcodes

PDF: http://www.eccv2016.org/files/posters/P-1A-10.pdf

Yoni Kasten, Hebrew University:

Gil Ben Artzi, Hebrew University of Jerusalem:

Shmuel Peleg, Hebrew University: http://www.cs.huji.ac.il/~peleg/

Michael Werman: http://www.cs.huji.ac.il/~werman/

【Object tracking】P-1A-27.   A Benchmark and Simulator for UAV Tracking

PDF: http://www.eccv2016.org/files/posters/P-1A-27.pdf

Matthias Mueller, KAUST:

Bernard Ghanem, KAUST:

Neil Smith, KAUST:

【Object tracking】P-1A-45.   Learning to Track at 100 FPS with Deep Regression Networks

PDF: http://www.eccv2016.org/files/posters/P-1A-45.pdf

David Held, UC Berkeley:

Sebastian Thrun, Stanford:

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【Object tracking】D-1A-48. Real-Time Monocular Segmentation and Pose Tracking of Multiple Objec

Henning Tjaden, Rhein Main University of Applied Sciences:

Ulrich Schwanecke, Rhein Main University of Applied Sciences:

Elmar Schömer, Johannes Gutenberg Universität Mainz:

【Object tracking】D-1A-49. Live Template-based 3D tracking and 3D reconstruction of deformable objects in 2D vide

Toby Collins, ALCo V, Université d’Auvergne:

Adrien Bartoli, ALCo V, Université d’Auvergne:

【Object tracking】P-1B-23.   Real-time Joint Tracking of a Hand Manipulating an Object from RGB-D Input

PDF: http://www.eccv2016.org/files/posters/P-1B-23.pdf

Srinath Sridhar, MPI for Informatics:

Franziska Mueller, MPI Informatics:

Michael Zollhoefer, MPI Informatics:

Dan Casas, MPI:

Antti Oulasvirta, Aalto University:

Christian Theobalt, MPI Informatics:

【Object tracking】P-2B-24.   Distractor-supported single target tracking in extremely cluttered scenes

PDF: http://www.eccv2016.org/files/posters/P-2B-24.pdf

Jingjing Xiao, University of Birmingham:

LINBO QIAO,:

Rustam Stolkin,:

Aleš Leonardis:

【Object tracking】P-2B-42.   Real-Time Monocular Segmentation and Pose Tracking of Multiple Objects

PDF: http://www.eccv2016.org/files/posters/P-2B-42.pdf

Henning Tjaden, Rhein Main University of Applied Sciences:

Ulrich Schwanecke, Rhein Main University of Applied Sciences:

Elmar Schömer, Johannes Gutenberg University Mainz:

【Object tracking】D-2B-49. Facial Tracki

Nial Stewart, ULSee Inc.:

【Object tracking】P-3A-47.   Tracking Persons-of-Interest via Adaptive Discriminative Features

PDF: http://www.eccv2016.org/files/posters/P-3A-47.pdf

Shun Zhang, Xi’an Jiaotong University:

Yihong Gong,:

Jia-Bin Huang, University of Illinois at Urbana-Champaign:

Jongwoo Lim, Hanyang University:

Jinjun Wang,:

Narendra Ahuja, University of Illinois at Urbana-Champaign: http://vision.ai.illinois.edu/publications.htm

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Object tracking】P-3B-23.   A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets

PDF: http://www.eccv2016.org/files/posters/P-3B-23.pdf

Carsten Haubold, University of Heidelberg:

Janez Ales,:

Steffen Wolf,:

Fred Hamprecht, Heidelberg University:

【Object tracking】P-3C-10.   Tracking Completion

PDF: http://www.eccv2016.org/files/posters/P-3C-10.pdf

Yao Sui, University of Kansas:

Guanghui Wang, University of Kansas:

Yafei Tang, China Unicom Research:

Li Zhang, Tsinghua University: http://pages.cs.wisc.edu/~lizhang/

【Object tracking】P-3C-37.   Cascaded Continuous Regression for Real-time Incremental Face Tracking

PDF: http://www.eccv2016.org/files/posters/P-3C-37.pdf

Enrique Sánchez-Lozano, University of Nottingham:

Brais Martinez, University of Nottingham:

Georgios Tzimiropoulos, Nottingham University:

Michel Valstar, Nottingham University:

【Object tracking】P-3C-38.   Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning

PDF: http://www.eccv2016.org/files/posters/P-3C-38.pdf

Yao Sui, University of Kansas:

Ziming Zhang, Boston University:

Guanghui Wang, University of Kansas:

Yafei Tang, China Unicom Research:

Li Zhang, Tsinghua University: http://pages.cs.wisc.edu/~lizhang/

【Object tracking】P-3C-45.   Improving Multi-Frame Data Association with Sparse Representations for Robust Near-Online Multi-Object Tracking

PDF: http://www.eccv2016.org/files/posters/P-3C-45.pdf

Loïc Fagot-Bouquet, CEA LIST:

Romaric Audigier, CEA LIST:

Yoann Dhome, CEA LIST:

Frédéric Lerasle, LAAS CNRS:

【Object tracking】D-3C-48. Aerial Tracking Evaluation using Unreal Engine 4 and VR

Matthias Mueller, King Abdullah University of Science and Technology:

Neil Smith, King Abdullah University of Science and Technology:

Bernard Ghanem, KAUST:

【Object tracking】S-4A-05.   Target Response Adaptation for Correlation Filter Tracking

PDF: http://www.eccv2016.org/files/posters/S-4A-05.pdf

Adel Bibi, KAUST:

Matthias Mueller, KAUST:

Bernard Ghanem, KAUST:

【Object tracking】P-4A-31.   CDT: Cooperative Detection and Tracking for Tracing Multiple Objects in Video Sequences

PDF: http://www.eccv2016.org/files/posters/P-4A-31.pdf

Hanul Kim, Korea university:

Chang-Su Kim, Korea University:

【Object tracking】O-4B-03.   Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

PDF: http://www.eccv2016.org/files/posters/O-4B-03.pdf

Martin Danelljan, Linköping University:

Andreas Robinson, Linköping University:

Fahad Khan, Linkoping University, Sweden:

Michael Felsberg, Link_ping University:

【Action recognition】P-1A-17.   Real-time RGB-D Activity Prediction by Soft Regression

PDF: http://www.eccv2016.org/files/posters/P-1A-17.pdf

Jian-Fang Hu, Sun Yat-sen University:

Wei-Shi Zheng,:

Lianyang Ma,:

Gang Wang,:

Jianhuang Lai:

【Action recognition】P-1A-25.   Learning Models for Actions and Person-Object Interactions with Transfer to Question Answering

PDF: http://www.eccv2016.org/files/posters/P-1A-25.pdf

Arun Mallya, UIUC:

Svetlana Lazebnik: http://www.cs.illinois.edu/homes/slazebni/

【Action recognition】P-1A-31.   Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding

PDF: http://www.eccv2016.org/files/posters/P-1A-31.pdf

Gunnar Sigurdsson, Carnegie Mellon University:

Gul Varol, INRIA:

Xiaolong Wang, CMU:

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

Ivan Laptev,: http://www.di.ens.fr/~laptev/index.html

Abhinav Gupta: http://www.cs.cmu.edu/~abhinavg/

【Action recognition】P-1B-26.   Multi-Task Zero-Shot Action Recognition with Prioritised Data Augmentation

PDF: http://www.eccv2016.org/files/posters/P-1B-26.pdf

Xun Xu, Queen Mary University of Londo:

Timothy Hospedales, Queen Mary University of London:

Shaogang Gong, Queen Mary University: http://www.eecs.qmul.ac.uk/~sgg/

【Action recognition】P-2A-13.   Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation

PDF: http://www.eccv2016.org/files/posters/P-2A-13.pdf

Colin Lea, Johns Hopkins University:

Austin Reiter, Johns Hopkins University:

Rene Vidal, Johns Hopkins University: http://cis.jhu.edu/~rvidal/

Gregory Hager, Johns Hopkins University:

【Action recognition】P-2A-38.   Multi-label Active Learning Based on Maximum Correntropy Criterion: Towards Robust and Discriminative Labeling

PDF: http://www.eccv2016.org/files/posters/P-2A-38.pdf

Zengmao Wang, Wuhan University:

Bo Du,:

Lefei Zhang, Wuhan University:

Liangpei Zhang, Wuhan University:

Meng Fang,:

Dacheng Tao, University of Technology, Sydney:

【Action recognition】P-2B-10.   DAPs: Deep Action Proposals for Action Understanding

PDF: http://www.eccv2016.org/files/posters/P-2B-10.pdf

Victor Escorcia, KAUST:

FABIAN CABA HEILBRON, KAUST:

Juan Carlos Niebles, Stanford University:

Bernard Ghanem, KAUST:

【Action recognition】P-2B-13.   Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

PDF: http://www.eccv2016.org/files/posters/P-2B-13.pdf

Jun Liu, Nanyang Technological University:

Amir Shahroudy, Nanyang Technological University:

Dong Xu,: http://www.ntu.edu.sg/home/dongxu/

Gang Wang:

【Action recognition】P-2B-19.   Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons

PDF: http://www.eccv2016.org/files/posters/P-2B-19.pdf

Piotr Koniusz, NICTA:

Anoop Cherian, ANU:

Fatih Porikli, ANU / NICTA: http://www.porikli.com/

【Action recognition】P-2B-25.   Connectionist Temporal Modeling for Weakly Supervised Action Labeling

PDF: http://www.eccv2016.org/files/posters/P-2B-25.pdf

De-An Huang, Stanford University:

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

Juan Carlos Niebles, Stanford University:

【Action recognition】P-2B-29.   Hierarchical Dynamic Parsing and Encoding for Action Recognition

PDF: http://www.eccv2016.org/files/posters/P-2B-29.pdf

Bing Su, Chinese Academy of Sciences:

JIAHUAN ZHOU, Northwestern University:

Xiaoqing Ding, Tsinghua University:

Hao Wang, Chinese Academy of Sciences:

Ying Wu, Northwestern University:

【Action recognition】P-3A-14.   Multi-region two-stream R-CNN for action detection

PDF: http://www.eccv2016.org/files/posters/P-3A-14.pdf

Xiaojiang Peng, INRIA:

Cordelia Schmid: http://lear.inrialpes.fr/~schmid/

【Action recognition】P-3A-31. Action Snapping: Motion-based Video Synchronizati

Jean-Charles Bazin, ETHZ:

Alexander Sorkine-Hornung, Disney Research Zurich:

【Action recognition】P-3A-38. Online Action Detecti

Roeland De Geest , KU Leuven:

Stratis Gavves, University of Amsterdam:

Amir Ghodrati,:

Zhenyang Li,:

Cees Snoek, University of Amsterdam:

Tinne Tuytelaars, KU Leuven: http://homes.esat.kuleuven.be/~tuytelaa/

【Action recognition】P-3B-12.   Graph Based Skeleton Motion Representation and Similarity Measurement for Action Recognition

PDF: http://www.eccv2016.org/files/posters/P-3B-12.pdf

Pei Wang, Chinese Academy of Sciences:

Chunfeng Yuan,:

Weiming Hu,:

Bing Li,:

yanning Zhang, Northwestern Polytechnical University:

【Action recognition】P-3B-31.   Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition

PDF: http://www.eccv2016.org/files/posters/P-3B-31.pdf

Cesar De Souza, Xerox Research Center Europe:

Adrien Gaidon,:

Eleonora Vig, German Aerospace Center:

Antonio Lopez, Centro de Visio per Computador, UAB:

【Action recognition】P-3B-32.   Human pose estimation via Convolutional Part Heatmap Regression

PDF: http://www.eccv2016.org/files/posters/P-3B-32.pdf

Adrian Bulat, University of Nottingham:

Georgios Tzimiropoulos, Nottingham University:

【Action recognition】P-3B-36. Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video

Yu-Chuan Su, University of Texas at Austin:

Kristen Grauman, University of Texas at Austin: http://www.cs.utexas.edu/~grauman/

【Action recognition】P-3B-42.   Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

PDF: http://www.eccv2016.org/files/posters/P-3B-42.pdf

Limin Wang, ETHZ:

Yuanjun Xiong, The Chinese University of HK:

Zhe Wang, SIAT, CAS:

Yu Qiao, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences:

Dahua Lin, CUHK: http://dahua.me/

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

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

【Action recognition】P-3B-47.   Towards Viewpoint Invariant 3D Human Pose Estimation

PDF: http://www.eccv2016.org/files/posters/P-3B-47.pdf

Albert Haque, Stanford University:

Boya Peng, Stanford University:

Zelun Luo, Stanford University:

Alexandre Alahi, Stanford University:

Serena Yeung, Stanford University:

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

【Action recognition】P-3C-19.   Spatial Attention Deep Net with Partial PSO for Hierarchical Hybrid Hand Pose Estimation

PDF: http://www.eccv2016.org/files/posters/P-3C-19.pdf

Qi Ye,:

Shanxin Yuan, Imperial College London:

Tae-Kyun Kim, Imperial College London:

【Action recognition】P-3C-27.   Stacked Hourglass Networks for Human Pose Estimation

PDF: http://www.eccv2016.org/files/posters/P-3C-27.pdf

Alejandro Newell, University of Michigan:

Kaiyu Yang, University of Michigan:

Jia Deng, University of Michigan:

【Action recognition】P-4A-30.   RNN Fisher Vectors for Action Recognition and Image Annotation

PDF: http://www.eccv2016.org/files/posters/P-4A-30.pdf

Guy Lev,:

Gil Sadeh,:

Benjamin Klein, Tel Aviv University:

Lior Wolf:

【Action recognition】P-4A-45.   Online Human Action Detection using Joint Classification-Regression Recurrent Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-4A-45.pdf

Yanghao Li, Peking University:

Cuiling Lan, Microsoft Research:

Junliang Xing, Chinese Academy of Sciences:

Wenjun Zeng, Microsoft Research:

Chunfeng Yuan,:

Jiaying Liu, Peking University:

【Action recognition】O-4B-01.   Spot On: Action Localization from Pointly-Supervised Proposals

PDF: http://www.eccv2016.org/files/posters/O-4B-01.pdf

Pascal Mettes, University of Amsterdam:

Jan van Gemert, Delft University of Technology:

Cees Snoek, University of Amsterdam:

【Action recognition】O-4B-04.   Look-ahead before you leap: end-to-end active recognition by forecasting the effect of motion

PDF: http://www.eccv2016.org/files/posters/O-4B-04.pdf

Dinesh Jayaraman, UT Austin:

Kristen Grauman, University of Texas at Austin: http://www.cs.utexas.edu/~grauman/

【Action recognition】S-4B-06.   Globally Continuous and Non-Markovian Activity Analysis from Videos

PDF: http://www.eccv2016.org/files/posters/S-4B-06.pdf

He Wang, Disney Research LA:

Carol O’Sullivan, Trinity College Dublin:

【Crowd analysis】P-3C-41.   Crossing-line Crowd Counting with Two-phase Deep Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3C-41.pdf

Zhuoyi Zhao, CUHK:

Hongsheng Li, CUHK:

Rui Zhao, The Chinese University of Hong Kong:

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

【Human detection】P-1A-44.   Embedding Deep Metric for Person Re-identification A Study Against Large Variations

PDF: http://www.eccv2016.org/files/posters/P-1A-44.pdf

Hailin Shi, NLPR:

Yang Yang, Institute of Automation:

Xiangyu Zhu,:

Shengcai Liao, Institute of Automation, Chinese Academy of Sciences:

Zhen Lei,:

Wei-Shi Zheng,:

Stan Li: http://www.cbsr.ia.ac.cn/users/szli/

【Human detection】P-1B-12.   Human Re-identification in Crowd Videos using Personal, Social and Environmental Constraints

PDF: http://www.eccv2016.org/files/posters/P-1B-12.pdf

Shayan Modiri Assari, University of Central Florida:

Haroon Idrees, University of Central Florida:

Mubarak Shah, University of Central Florida: http://crcv.ucf.edu/people/faculty/shah.html

【Human detection】P-1B-20.   Person Re-identification by Unsupervised Graph Learning

PDF: http://www.eccv2016.org/files/posters/P-1B-20.pdf

Elyor Kodirov, QMUL:

Tao Xiang, Queen Mary University of London:

Zhenyong Fu,:

Shaogang Gong, Queen Mary University: http://www.eecs.qmul.ac.uk/~sgg/

【Human detection】P-1B-32.   Is Faster R-CNN Doing Well for Pedestrian Detection?

PDF: http://www.eccv2016.org/files/posters/P-1B-32.pdf

Liliang Zhang, Sun Yat-sen University:

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

Xiaodan Liang, Sun Yat-sen University:

Kaiming He, Microsoft Research Asia: http://research.microsoft.com/en-us/um/people/kahe/

【Human detection】P-1B-34.   Deep Attributes Driven Person Re-identification

PDF: http://www.eccv2016.org/files/posters/P-1B-34.pdf

Chi Su, Peking University:

Shiliang Zhang, Peking University:

Junliang Xing, Chinese Academy of Sciences:

Wen Gao, Peking University: http://www.jdl.ac.cn/

Qi Tian: http://www.cs.utsa.edu/~qitian/

【Human detection】P-2A-12.   Faceless Person Recognition; Privacy Implications in Social Media

PDF: http://www.eccv2016.org/files/posters/P-2A-12.pdf

Seong Joon Oh, MPI-INF:

Rodrigo Benenson, MPI Informatics: http://rodrigob.github.io/

Mario Fritz,: https://scalable.mpi-inf.mpg.de/

Bernt Schiele: http://www.d2.mpi-inf.mpg.de/schiele/

【Human detection】P-3A-21.   Temporal Model Adaptation for Person Re-Identification

PDF: http://www.eccv2016.org/files/posters/P-3A-21.pdf

Niki Martinel, University of Udine:

Abir Das, University of Massachusetts Lowell:

Christian Micheloni, University of Udine:

Amit Roy-Chowdhury, UC Riverside:

【Human detection】P-3A-37.   Ego2Top: Matching Viewers in Egocentric and Top-view Videos

PDF: http://www.eccv2016.org/files/posters/P-3A-37.pdf

Shervin Ardeshir, University of Central Florida:

Ali Borji, University of Cenreal Florida: http://ilab.usc.edu/borji/

【Human detection】P-4A-22.   Person Re-Identification via Recurrent Feature Aggregation

PDF: http://www.eccv2016.org/files/posters/P-4A-22.pdf

Yichao Yan, Shanghai Jiaotong University:

Bingbing Ni, SJTU:

Zhichao Song,:

chao Ma,:

Yan Yan,:

xiaokang Yang, SJTU:

【Human parsing】P-1A-11.   Human pose estimation using deep consensus voting

PDF: http://www.eccv2016.org/files/posters/P-1A-11.pdf

Ita Lifshitz, Weizmann Inst.:

Ethan Fetaya, Weizmann Inst.:

Shimon Ullman, Weizmann Inst.:

【Human parsing】P-1A-16. Pedestrian Behavior Understanding and Prediction with Deep Neural Network

Shuai Yi, CUHK:

Hongsheng Li, CUHK:

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

【Human parsing】P-1B-19.   Fashion Landmark Detection in the Wild

PDF: http://www.eccv2016.org/files/posters/P-1B-19.pdf

Ziwei Liu, The Chinese Univ. of Hong Kong:

Sijie Yan, The Chinese Univ. of Hong Kong:

Ping Luo, The Chinese University of Hong Kong:

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

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

【Human parsing】P-2A-44.   Hand pose estimation from local surface normals

PDF: http://www.eccv2016.org/files/posters/P-2A-44.pdf

Chengde Wan, ETHZ:

Angela Yao, University of Bonn:

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

【Human parsing】D-2A-48. Multi-person Body Pose Estimati

Eldar Insafutdinov, Max Planck Institute for Informatics:

Leonid Pishchulin, Max Planck Institute for Informatics:

Evgeny Levinkov, Max Planck Institute for Informatics:

Bjoern Andres, Max Planck Institute for Informatics:

Mykhaylo Andriluka, Max Planck Institute for Informatics:

Bernt Schiele, Max Planck Institute for Informatics: http://www.d2.mpi-inf.mpg.de/schiele/

【Human parsing】P-2B-22.   Shape from Selfies : Human Body Shape Estimation using CCA Regression Forests

PDF: http://www.eccv2016.org/files/posters/P-2B-22.pdf

Endri Dibra, ETH Zurich:

Cengiz Oztireli, ETH Zurich:

Remo Ziegler, Vizrt:

Markus Gross, ETH Zurich:

【Human parsing】P-2B-43.   Estimation of Human Body Shape in Motion with Wide Clothing

PDF: http://www.eccv2016.org/files/posters/P-2B-43.pdf

Jinlong Yang, Inria:

Jean-Sebastien Franco, LJK, Université Grenoble Alpes, Inria:

Franck Hétroy-Wheeler, University Grenoble Alpes:

Stefanie Wuhrer, INRIA:

【Human parsing】P-3C-31.   Learning Social Etiquette: Human Trajectory Understanding in Crowded Scenes

PDF: http://www.eccv2016.org/files/posters/P-3C-31.pdf

Alexandre Robicquet, Stanford university:

Amir Sadeghian, stanford university:

Alexandre Alahi, Stanford University:

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【Human parsing】P-4A-21.   Human Attribute Recognition by Deep Hierarchical Contexts

PDF: http://www.eccv2016.org/files/posters/P-4A-21.pdf

Yining Li, IE, CUHK:

Chen Huang, The Chinese University of Hong Kong:

Chen-Change Loy, the Chinese University of Hong Kong:

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

【Human parsing】S-4B-08.   Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

PDF: http://www.eccv2016.org/files/posters/S-4B-08.pdf

Federica Bogo, Max Planck Institute Tuebingen:

Angjoo Kanazawa, University of Maryland:

Christoph Lassner, BCCN Tübingen:

Peter Gehler,:

Javier Romero, MPI Intelligent Systems Tuebingen:

Michael Black: http://ps.is.tue.mpg.de/person/black

【Human parsing】P-4B-13.   Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net

PDF: http://www.eccv2016.org/files/posters/P-4B-13.pdf

Fangting Xia, UCLA:

Peng Wang, UCLA:

Liang-Chieh Chen, UCLA:

Alan Yuille, UCLA: http://www.stat.ucla.edu/~yuille/

【Human parsing】P-4B-19.   A Sequential Approach to 3D Human Pose Estimation: Separation of Localization and Identification of Body Joints

PDF: http://www.eccv2016.org/files/posters/P-4B-19.pdf

Hoyub Jung, HUFS:

Yumin Suh, Seoul National University:

Gyeongsik Moon, Seoul National University:

Kyoung Mu Lee: http://cv.snu.ac.kr/kmlee/

【Human parsing】P-4B-24.   Robust Face Alignment Using a Mixture of Invariant Experts

PDF: http://www.eccv2016.org/files/posters/P-4B-24.pdf

Oncel Tuzel, MERL:

Tim Marks, MERL:

Salil Tambe:

【Human parsing】P-4B-30.   Deeper Cut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model

PDF: http://www.eccv2016.org/files/posters/P-4B-30.pdf

Eldar Insafutdinov, Max-Planck Institute for Infor:

Leonid Pishchulin, MPI Informatik:

Bjoern Andres, Max-Planck Institute for Informatics:

Mykhaylo Andriluka, Max-Planck Institute for Informatics:

Bernt Schiele: http://www.d2.mpi-inf.mpg.de/schiele/

【Face recognition】P-2A-16.   MS-Celeb-1M: A Dataset and Benchmark for Large Scale Face Recognition

PDF: http://www.eccv2016.org/files/posters/P-2A-16.pdf

Yandong Guo, Microsoft Corporation:

Lei Zhang, Microsoft Corporation: http://www4.comp.polyu.edu.hk/~cslzhang/

Yuxiao Hu, Microsoft Corporation:

Xiaodong He, Microsoft Corporation:

Jianfeng Gao, Microsoft Corporation:

【Face recognition】P-3B-45.   Face recognition using a unified 3D morphable model

PDF: http://www.eccv2016.org/files/posters/P-3B-45.pdf

GUOSHENG HU, INRIA:

fei Yan,:

chi-Ho Chan, CVSSP, University of Surrey:

Weihong Deng, BUPT:

william Christmas, CVSSP:

Josef Kittler, University of Surrey:

Neil Robertson, Queen’s University of Belfast:

【Face detection】P-2A-25.   Joint Face Representation Adaptation and Clustering in Videos

PDF: http://www.eccv2016.org/files/posters/P-2A-25.pdf

Zhanpeng Zhang, The Chinese University of HK:

Ping Luo, The Chinese University of Hong Kong:

Chen-Change Loy, the Chinese University of Hong Kong:

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

【Face detection】P-2A-34.   Grid Loss: Detecting Occluded Faces

PDF: http://www.eccv2016.org/files/posters/P-2A-34.pdf

Michael Opitz, Graz University of Technology:

Georg Waltner, TU Graz:

Georg Poier, Graz University of Technology:

Horst Possegger, Graz University of Technology:

Horst Bischof, Graz University of Technology: http://www.icg.tugraz.at/Members/bischof

【Face detection】P-2A-36.   Face Detection with End-to-End Integration of a Conv Net and a 3D Model

PDF: http://www.eccv2016.org/files/posters/P-2A-36.pdf

Yunzhu Li, Peking University:

Benyuan Sun, PKU:

Tianfu Wu, UCLA:

Yizhou Wang, Peking University:

【Face detection】P-3A-29.   Supervised Transformer Network for Efficient Face Detection

PDF: http://www.eccv2016.org/files/posters/P-3A-29.pdf

Dong Chen, Microsoft Research:

Gang Hua, Microsoft Research: http://www.cs.stevens.edu/~ghua/

Fang Wen, Microsoft Research:

Jian Sun, Microsoft Research China: http://research.microsoft.com/en-us/groups/vc/

【Face detection】S-4B-09.   Do We Really Need to Collect Millions of Faces for Effective Face Recognition?

PDF: http://www.eccv2016.org/files/posters/S-4B-09.pdf

Iacopo Masi, USC:

Anh Tran, USC:

Tal Hassner, Open Univ Israel:

Jatuporn Leksut, USC:

Gerard Medioni, University of Southern California:

【Face parsing】O-1A-03.   A Recurrent Encoder-Decoder Network for Sequential Face Alignment

PDF: http://www.eccv2016.org/files/posters/O-1A-03.pdf

Xi Peng, Rutgers University:

Rogerio Feris, IBM Research Center, USA: http://rogerioferis.com/

Xiaoyu Wang, Snapchat Research:

Dimitris Metaxas, Rutgers University:

【Face parsing】O-1A-04.   Robust Facial Landmark Detection via Recurrent Attentive-Refinement Networks

PDF: http://www.eccv2016.org/files/posters/O-1A-04.pdf

Shengtao Xiao, National University of Singapore:

Jiashi Feng, NUS:

Junliang Xing, Chinese Academy of Sciences:

Hanjiang Lai, SUN YAT-SEN UNIVERSITY:

Shuicheng Yan, National University of Singapore: http://www.lv-nus.org/index.html

Ashraf Kassim, National University of Singapore:

【Face parsing】P-1A-18.   A 3D Morphable Eye Region Model for Gaze Estimation

PDF: http://www.eccv2016.org/files/posters/P-1A-18.pdf

Erroll Wood, University of Cambridge:

Tadas Baltrušaitis, Carnegie Mellon University:

Louis-Philippe Morency, Carnegie Mellon University:

Peter Robinson, University of Cambridge:

Andreas Bulling, Max Planck Institute for Informatics:

【Face parsing】S-1B-09.   Modeling Context in Referring Expressions

PDF: http://www.eccv2016.org/files/posters/S-1B-09.pdf

Licheng Yu, University of North Carolina:

Patrick Poirson,:

Shang Yang,:

Alex Berg,:

Tamara Berg, University on North Carolina:

【Face parsing】P-1B-31.   Peak-Piloted Deep Network for Facial Expression Recognition

PDF: http://www.eccv2016.org/files/posters/P-1B-31.pdf

Xiangyun Zhao, University of California, San Diego:

Xiaodan Liang, Sun Yat-sen University:

Luoqi Liu, Qihoo/360:

Teng Li, Anhui University:

Yugang Han, 360 AI Institute:

Nuno Vasconcelos,: http://www.svcl.ucsd.edu/

Shuicheng Yan: http://www.lv-nus.org/index.html

【Face parsing】D-1B-49. ZFa

László A. Jeni, Carnegie Mellon University:

Jeffrey F. Cohn, Carnegie Mellon University and University of Pittsburgh:

Takeo Kanade, Carnegie Mellon University:

【Face parsing】P-3A-23.   MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes

PDF: http://www.eccv2016.org/files/posters/P-3A-23.pdf

Ethan Rudd, UCCS:

Manuel Günther, UCCS:

Terrance Boult, University of Colorado Colorado Springs:

【Face parsing】P-4A-38.   3D Mask Face Anti-spoofing with Remote Photoplethysmography

PDF: http://www.eccv2016.org/files/posters/P-4A-38.pdf

Siqi Liu, Hong Kong Baptist University:

Pong Chi YUEN, Hong Kong Baptist University:

Shengping Zhang, Harbin Institute of Technology:

Guoying Zhao, University of Oulu:

【Face parsing】S-4B-07.   Joint Face Alignment and 3D Face Reconstruction

PDF: http://www.eccv2016.org/files/posters/S-4B-07.pdf

Feng Liu, Sichuan University: http://web.cecs.pdx.edu/~fliu/

Qijun Zhao, Sichuan University:

Dan Zeng, Sichuan University:

Xiaoming Liu, Michigan State University:

【Object recognition】O-1B-01.   Ambient sound provides supervision for visual learning

PDF: http://www.eccv2016.org/files/posters/O-1B-01.pdf

Andrew Owens, MIT:

Jiajun Wu, MIT:

Josh Mcdermott, MIT:

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

William Freeman, MIT: http://people.csail.mit.edu/billf/

【Object recognition】S-1B-05.   The Curious Robot: Learning Visual Representations via Physical Interactions

PDF: http://www.eccv2016.org/files/posters/S-1B-05.pdf

Lerrel Pinto, Carnegie Mellon University:

Dhiraj Gandhi,:

Yuanfeng Han,:

Yong-Lae Park,:

Abhinav Gupta: http://www.cs.cmu.edu/~abhinavg/

【Object recognition】S-1B-08.   An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild

PDF: http://www.eccv2016.org/files/posters/S-1B-08.pdf

Wei-Lun Chao, USC:

Soravit Changpinyo, U. of Southern California:

Boqing Gong, University of Central Florida:

Fei Sha, UCLA:

【Object recognition】P-2A-26.   Uncovering Symmetries in Polynomial Systems

PDF: http://www.eccv2016.org/files/posters/P-2A-26.pdf

Viktor Larsson, Lund University:

Kalle Astroem, Lund University:

【Object recognition】P-2A-29.   The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition

PDF: http://www.eccv2016.org/files/posters/P-2A-29.pdf

Jonathan Krause, Stanford University:

Benjamin Sapp, Google:

Andrew Howard, Google:

Howard Zhou, Google:

Alexander Toshev, Google:

Tom Duerig, Google:

James Philbin, Google:

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

【Object recognition】P-2B-12.   Reliable Attribute-Based Object Recognition Using High Predictive Value Classifiers

PDF: http://www.eccv2016.org/files/posters/P-2B-12.pdf

Wentao Luan, University of Maryland:

Yezhou Yang, University of Maryland: http://www.umiacs.umd.edu/~yzyang/

Cornelia Fermuller, University of Maryland:

John Baras, University of Maryland:

【Object recognition】P-2B-15.   Webly-supervised Video Recognition by Mutually Voting for Relevant Web Images and Web Video Frames

PDF: http://www.eccv2016.org/files/posters/P-2B-15.pdf

Chuang Gan, Tsinghua University:

Chen Sun, USC:

Lixin Duan, Amazon:

Boqing Gong, University of Central Florida:

【Object recognition】P-2B-41.   Human-In-The-Loop Person Re-Identification

PDF: http://www.eccv2016.org/files/posters/P-2B-41.pdf

Hanxiao Wang, Queen Mary, Univ. of London:

Shaogang Gong, Queen Mary University: http://www.eecs.qmul.ac.uk/~sgg/

Xiatian Zhu,:

Tao Xiang, Queen Mary University of London:

【Object recognition】P-2B-47.   Recognition from Hand Cameras: A Revisit with Deep Learning

PDF: http://www.eccv2016.org/files/posters/P-2B-47.pdf

Cheng-Sheng Chan,:

Shou-Zhong CHEN,:

Pei-Xuan Xie,:

CHIUNG-CHIH CHANG,:

Min Sun, National Tsing Hua University:

【Object recognition】P-3A-10.   Unsupervised Visual Representation Learning by Graph-based Consistent Constraints

PDF: http://www.eccv2016.org/files/posters/P-3A-10.pdf

Dong Li, Tsinghua University:

Wei-Chih Hung, USC:

Jia-Bin Huang, University of Illinois at Urbana-Champaign:

Shengjin Wang, wgsgj@tsinghua.edu.cn:

Narendra Ahuja, University of Illinois at Urbana-Champaign: http://vision.ai.illinois.edu/publications.htm

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Object recognition】D-3A-48. Deep XCam: Very Fast CNN-based Mobile Applications: Multiple Style Transfer and Object Recognition

Ryusuke Tanno, The University of Electro-Communication, Tokyo:

Wataru Shimoda, The University of Electro-Communication, Tokyo:

Keiji Yanai, The University of Electro-Communication, Tokyo:

【Object recognition】S-3C-08.   Object Net3D: A Large Scale Database for 3D Object Recognition

PDF: http://www.eccv2016.org/files/posters/S-3C-08.pdf

Yu Xiang, University of Michigan:

Wonhui Kim, University of Michigan:

Wei Chen, Stanford University:

Jingwei Ji, Stanford University:

Christopher Choy, Stanford University:

Hao Su, Stanford:

Roozbeh Mottaghi, Allen Institute for AI: http://www.cs.stanford.edu/~roozbeh/

Leonidas J. Guibas,:

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【Object recognition】P-3B-19.   Counting in The Wild

PDF: http://www.eccv2016.org/files/posters/P-3B-19.pdf

Carlos Arteta, Oxford University:

Victor Lempitsky, Skolkovo Institute of Science and Technology:

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

【Object recognition】P-3B-22.   Zero-Shot Recognition via Structured Prediction

PDF: http://www.eccv2016.org/files/posters/P-3B-22.pdf

Ziming Zhang, Boston University:

Venkatesh Saligrama,:

【Object recognition】P-3B-26.   Towards perspective-free object counting with deep learning

PDF: http://www.eccv2016.org/files/posters/P-3B-26.pdf

Daniel Oñoro Rubio, University of Alcalá:

Roberto Lopez-Sastre, University of Alcala:

【Object recognition】P-3B-27.   Information Bottleneck Domain Adaptation with Privileged Information for Visual Recognition

PDF: http://www.eccv2016.org/files/posters/P-3B-27.pdf

Saeid Motiian, West Virginia University:

Gianfranco Doretto, West Virginia University:

【Object recognition】P-3C-12.   Online Adaptation for Joint Scene and Object Classification

PDF: http://www.eccv2016.org/files/posters/P-3C-12.pdf

Md Jawadul Bappy, University of California, Riverside:

Sujoy Paul, University of California, Riverside:

Amit Roy-Chowdhury, UC Riverside:

【Object recognition】S-4A-09.   Learning a Predictable and Generative Vector Representation for Objects

PDF: http://www.eccv2016.org/files/posters/S-4A-09.pdf

Rohit Girdhar, CMU:

David Fouhey, Carnegie Mellon University:

Mikel Rodriguez, MITRE INRIA:

Abhinav Gupta: http://www.cs.cmu.edu/~abhinavg/

【Object recognition】P-4A-13.   Domain Adaptive Fisher Vector for Visual Recognition

PDF: http://www.eccv2016.org/files/posters/P-4A-13.pdf

Li Niu, NTU:

Jianfei Cai,: http://www3.ntu.edu.sg/home/asjfcai/

Dong Xu: http://www.ntu.edu.sg/home/dongxu/

【Object recognition】P-4A-37.   Learning Visual Features from Large Weakly Supervised Data

PDF: http://www.eccv2016.org/files/posters/P-4A-37.pdf

Armand Joulin, Facebook AI Research:

Laurens van der Maaten,:

Allan Jabri, Facebook AI Research:

Nicolas Vasilache, Facebook AI Research:

【Object recognition】P-4B-18.   Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification

PDF: http://www.eccv2016.org/files/posters/P-4B-18.pdf

Maxime Bucher, ONERA:

Stephane Herbin, ONERA:

Frederic Jurie, University of Caen:

【Object recognition】P-4B-20.   A Novel Tiny Object Recognition Algorithm Based on Unit Statistical Curvature Feature

PDF: http://www.eccv2016.org/files/posters/P-4B-20.pdf

Yimei Kang, College of Software, Beihang University:

Xiang Li, College of Software, Beihang University:

【Object recognition】P-4B-32.   Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

PDF: http://www.eccv2016.org/files/posters/P-4B-32.pdf

Mehdi Noroozi, University of Bern:

Paolo Favaro:

【Object recognition】P-4B-33.   COCO Attributes: Attributes for People, Animals, and Objects

PDF: http://www.eccv2016.org/files/posters/P-4B-33.pdf

Genevieve Patterson, Microsoft Research:

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

【Object recognition】P-4B-39.   Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experiment Design in Neuroimaging

PDF: http://www.eccv2016.org/files/posters/P-4B-39.pdf

Won Hwa Kim, UW-Madison:

Seong Jae Hwang, UW-Madison:

Nagesh Adluru, UW-Madison:

Sterling Johnson, UW-Madison:

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

【Object recognition】P-4B-40.   A Benchmark for Automatic Visual Classification of Clinical Skin Disease Images

PDF: http://www.eccv2016.org/files/posters/P-4B-40.pdf

SUN Xiao Xiao, Nan Kai University:

Jufeng Yang, Nankai University:

Ming Sun, Nan Kai Unverisity:

Kai Wang, Nankai University:

【Object detection】S-1B-06.   Image Co-localization by Mimicking a Good Detector’s Confidence Score Distribution

PDF: http://www.eccv2016.org/files/posters/S-1B-06.pdf

Yao Li, University of Adelaide:

Lingqiao Liu, University of Adelaide:

Chunhua Shen, University of Adelaide:

Anton Van den Hengel, University of Adelaide:

【Object detection】P-1B-16.   Visual Motif Discovery via First-Person Vision

PDF: http://www.eccv2016.org/files/posters/P-1B-16.pdf

Ryo Yonetani, University of Tokyo:

Kris Kitani, Carnegie Mellon University:

Yoichi Sato:

【Object detection】P-1B-22.   DAVE: A Unified Framework for Fast Vehicle Detection and Annotation

PDF: http://www.eccv2016.org/files/posters/P-1B-22.pdf

Yi Zhou, Northumbria University:

Li Liu, Northumbria University:

Ling Shao, Northumbria University: http://lshao.staff.shef.ac.uk/

Matt Mellor, Createc Ltd.:

【Object detection】P-2B-38.   A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

PDF: http://www.eccv2016.org/files/posters/P-2B-38.pdf

Zhaowei Cai, ucsd.edu:

Quanfu Fan, IBM:

Rogerio Feris, IBM Research Center: http://rogerioferis.com/

Nuno Vasconcelos: http://www.svcl.ucsd.edu/

【Object detection】P-3A-39.   Cross-modal Supervision for Learning Active Speaker Detection in Video

PDF: http://www.eccv2016.org/files/posters/P-3A-39.pdf

Punarjay Chakravarty, KU Leuven:

Tinne Tuytelaars, KU Leuven: http://homes.esat.kuleuven.be/~tuytelaa/

【Object detection】P-3A-43.   Context Loc Net: Context-aware Deep Network Models for Weakly Supervised Localization

PDF: http://www.eccv2016.org/files/posters/P-3A-43.pdf

Vadim Kantorov, INRIA:

Maxime Oquab, INRIA:

Minsu Cho, INRA:

Ivan Laptev: http://www.di.ens.fr/~laptev/index.html

【Object detection】P-3B-11. Gated Bi-directional CNN for Object Detection

Xingyu Zeng, The Chinese University of Hong Kong:

Wanli Ouyang, Chinese University of Hong Kong: http://www.ee.cuhk.edu.hk/~wlouyang/

Bin Yang, NLPR, CASIA:

Junjie Yan, National Laboratory of Pattern Recognition, Chinese Academy of Sciences:

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

【Object detection】P-3B-40.   Carried Object Detection based on an Ensemble of Contour Exemplars

PDF: http://www.eccv2016.org/files/posters/P-3B-40.pdf

FARNOOSH GHADIRI, Laval University:

ROBERT BERGEVIN, Laval university:

GUILLAUME-ALEXANDRE BILODEAU, École Polytechnique de Montréal:

【Object detection】P-4A-47.   A Deep Learning-based Approach to Progressive Vehicle Re-identification for Urban Surveillance

PDF: http://www.eccv2016.org/files/posters/P-4A-47.pdf

Xinchen Liu, Beijing University of Posts and Telecommunication:

Wu Liu, Beijing University of Posts and Telecommunication:

Tao Mei, Microsoft Research Asia:

Huadong Ma, Beijing University of Posts and Telecommunication:

【Object detection】O-4B-02.   Detecting Engagement in Egocentric Video

PDF: http://www.eccv2016.org/files/posters/O-4B-02.pdf

Yu-Chuan Su, University of Texas at Austin:

Kristen Grauman, University of Texas at Austin: http://www.cs.utexas.edu/~grauman/

【Saliency detection】O-1A-02.   SSD: Single Shot Multi Box Detector

PDF: http://www.eccv2016.org/files/posters/O-1A-02.pdf

Wei Liu, UNC Chapel Hill:

Dragomir Anguelov, Zoox:

dumitru Erhan, Google:

Christian Szegedy, Google:

Scott Reed, University of Michigan, Ann-Arbor:

Cheng-Yang Fu, UNC Chapel Hill:

Alex Berg, UNC Chapel Hill:

【Saliency detection】P-2B-30.   Distinct Class Saliency Maps for Weakly Supervised Semantic Segmentation

PDF: http://www.eccv2016.org/files/posters/P-2B-30.pdf

Wataru Shimoda, The University of Electro-Communications, Tokyo:

Keiji Yanai, The University of Electro-Communications:

【Saliency detection】P-2B-44.   A Shape-based Approach for Salient Object Detection Using Deep Learning

PDF: http://www.eccv2016.org/files/posters/P-2B-44.pdf

Jongpil Kim, Rutgers Univ.:

Vladimir Pavlovic, Rutgers University:

【Saliency detection】O-3A-02.   Top-down Neural Attention by Excitation Backprop

PDF: http://www.eccv2016.org/files/posters/O-3A-02.pdf

Jianming Zhang:

Zhe Lin, Adobe Systems, Inc.: http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Jonathan Brandt:

Xiaohui Shen, Adobe:

Stan Sclaroff, Boston University:

【Saliency detection】O-3A-02.   Top-down Neural Attention by Excitation Backprop

PDF: http://www.eccv2016.org/files/posters/O-3A-02.pdf

Jianming Zhang:

Zhe Lin, Adobe Systems, Inc.: http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Jonathan Brandt:

Xiaohui Shen, Adobe:

Stan Sclaroff, Boston University:

【Saliency detection】P-3A-13.   Chained Predictions Using Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3A-13.pdf

Georgia Gkioxari,:

Navdeep Jaitly, Google:

Alexander Toshev, Google:

【Saliency detection】P-3A-19.   Saliency Detection with Recurrent Fully Convolutional Networks

PDF: http://www.eccv2016.org/files/posters/P-3A-19.pdf

Linzhao Wang:

Lijun Wang, Dalian University of Technology:

Huchuan Lu,: http://ice.dlut.edu.cn/lu/index.html

Pingping Zhang, Dalian University of Technolog:

Xiang Ruan:

【Saliency detection】P-3A-25.   Deep Deformation Network for Object Landmark Localization

PDF: http://www.eccv2016.org/files/posters/P-3A-25.pdf

Xiang Yu, NEC Labs:

Feng Zhou, NEC Lab:

Manmohan Chandraker, NEC Labs America:

【Saliency detection】P-3A-26.   Learning Visual Storylines with Skipping Recurrent Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3A-26.pdf

Gunnar Sigurdsson, Carnegie Mellon University:

Xinlei Chen, CMU:

Abhinav Gupta: http://www.cs.cmu.edu/~abhinavg/

【Saliency detection】P-3A-42.   A Discriminative Framework for Anomaly Detection in Large Videos

PDF: http://www.eccv2016.org/files/posters/P-3A-42.pdf

Allison Del Giorno, Carnegie Mellon University:

Martial Hebert, Carnegie Mellon University: http://www.cs.cmu.edu/~hebert/

Andrew Bagnell, Carnegie Mellon University:

Saliency detection】P-3C-25.   Kernelized Subspace Ranking for Saliency Detection

PDF: http://www.eccv2016.org/files/posters/P-3C-25.pdf

Tiantian Wang, Dalian Universityof Technology:

Lihe Zhang, Dalian Universityof Technology:

Huchuan Lu,: http://ice.dlut.edu.cn/lu/index.html

Chong Sun,:

Jinqing Qi, Dalian Universityof Technology:

【Saliency detection】P-3C-47.   Saliency Detection via Combining Region-Level and Pixel-Level Predictions with CNNs

PDF: http://www.eccv2016.org/files/posters/P-3C-47.pdf

Youbao Tang, Harbin Institute of Technology:

Xiangqian Wu, Harbin Institute of Technology:

【Saliency detection】P-4A-15.   Pattern Mining Saliency

PDF: http://www.eccv2016.org/files/posters/P-4A-15.pdf

Yuqiu Kong, Dalian University of Technolog:

Lijun Wang, Dalian University of Technology:

Xiuping Liu, Dalian University of Technology:

Huchuan Lu,: http://ice.dlut.edu.cn/lu/index.html

Xiang Ruan:

【Saliency detection】P-4A-33.   Angry Crowds: Detecting Violent Events in Videos

PDF: http://www.eccv2016.org/files/posters/P-4A-33.pdf

Seyed Sadegh Mohammadi, Istituto Italiano di Tecnologi:

Alessandro Perina, Microsoft:

Hamed Kiani,:

Vittorio Murino, Istituto Italiano di Tecnologia:

【Saliency detection】P-4A-44.   CATS: Co-saliency Activated Tracklet Selection for Video Co-localization

PDF: http://www.eccv2016.org/files/posters/P-4A-44.pdf

Koteswar Jerripothula, Nanyang Technological University:

Jianfei Cai,: http://www3.ntu.edu.sg/home/asjfcai/

Junsong Yuan, Nanyang Technological University:

【Saliency detection】P-4B-23.   Where should saliency models look next?

PDF: http://www.eccv2016.org/files/posters/P-4B-23.pdf

Zoya Bylinskii, MIT:

Adria Recasens, MIT:

Ali Borji, University of Central Flordia: http://ilab.usc.edu/borji/

Aude Oliva, MIT:

Antonio Torralba,: http://web.mit.edu/torralba/www/

Fredo Durand: http://people.csail.mit.edu/fredo/

【Saliency detection】P-4B-35.   Salient Deconvolutional Networks

PDF: http://www.eccv2016.org/files/posters/P-4B-35.pdf

Aravindh Mahendran, Oxford:

Andrea Vedaldi: http://www.robots.ox.ac.uk/~vedaldi/index.html

【Scene recognition】P-1A-47.   Semantic Clustering for Robust Fine-Grained Scene Recognition

PDF: http://www.eccv2016.org/files/posters/P-1A-47.pdf

Marian George, ETH Zurich:

Dixit Mandar, University of California, San Diego:

Gábor Zogg, ETH Zurich:

Nuno Vasconcelos: http://www.svcl.ucsd.edu/

【Scene recognition】P-1B-28.   Support Discrimination Dictionary Learning for Image Classification

PDF: http://www.eccv2016.org/files/posters/P-1B-28.pdf

Yang Liu, University of Cambridge:

Wei Chen, University of Cambridge:

Qingchao Chen, University College London:

Ian Wassell, University of Cambridge:

【Scene recognition】P-2B-17.   Generating Visual Explanations

PDF: http://www.eccv2016.org/files/posters/P-2B-17.pdf

Lisa Anne Hendricks, UC Berkeley:

Zeynep Akata,:

Marcus Rohrbach, UC Berkeley:

Jeff Donahue, UC Berkeley:

Bernt Schiele,: http://www.d2.mpi-inf.mpg.de/schiele/

Trevor Darrell: http://www.eecs.berkeley.edu/~trevor/

【Scene recognition】P-2B-31. A Diagram Is Worth A Dozen Imag

Aniruddha Kembhavi, AI2:

Michael Salvato, Allen Institute for Artificial:

Eric Kolve, Allen Institute for AI:

Minjoon Seo, University of Washington:

Hannaneh Hajishirzi, University of Washington:

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

【Scene recognition】O-3A-01. XNOR-Net: Image Net Classification Using Binary Convolutional Neural Networ

Mohammad Rastegari, AI2:

Vicente Ordonez, Allen Institute for AI:

Joe Redmon:

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

【Scene recognition】  O-3A-01. XNOR-Net: Image Net Classification Using Binary Convolutional Neural Networks

Mohammad Rastegari, AI2:

Vicente Ordonez, Allen Institute for AI:

Joe Redmon:

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

【Scene recognition】P-3A-30.   A Geometric Approach to Image Labeling

PDF: http://www.eccv2016.org/files/posters/P-3A-30.pdf

Freddie Astrom, Heidelberg University:

Stefania Petra,:

Bernhard Schmitzer, Université Paris-Dauphine:

Christoph Schnoerr, Heidelberg University:

【Scene recognition】P-3B-17.   Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering

PDF: http://www.eccv2016.org/files/posters/P-3B-17.pdf

Huijuan Xu, UMass Lowell:

Kate Saenko, University of Massachusetts Lowel:

【Scene recognition】P-3B-21.   Network of Experts for Large-Scale Image Categorization

PDF: http://www.eccv2016.org/files/posters/P-3B-21.pdf

Karim Ahmed, Dartmouth:

Mohammad Haris Baig, Dartmouth College:

Lorenzo Torresani, Dartmouth College:

【Scene recognition】P-3B-39.   An Uncertain Future: Forecasting from Static Images using Variational Autoencoders

PDF: http://www.eccv2016.org/files/posters/P-3B-39.pdf

Jacob Walker, Carnegie Mellon University:

Carl Doersch, Carnegie Mellon University:

Abhinav Gupta,: http://www.cs.cmu.edu/~abhinavg/

Martial Hebert, Carnegie Mellon University: http://www.cs.cmu.edu/~hebert/

【Scene recognition】P-3C-18.   SPLea P: Soft Pooling of Learned Parts for Image Classification

PDF: http://www.eccv2016.org/files/posters/P-3C-18.pdf

Praveen Kulkarni, Technicolor:

Frederic Jurie, University of Caen:

joaquin Zepeda, Technicolor:

Patrick Perez, Technicolor, France:

Louis Chevallier, Technicolor:

【Scene recognition】P-3C-42.   Revisiting Visual Question Answering Baselines

PDF: http://www.eccv2016.org/files/posters/P-3C-42.pdf

Allan Jabri, Facebook AI Research:

Armand Joulin, Facebook AI Research:

Laurens van der Maaten:

【Scene recognition】P-4A-26.   Efficient Large Scale Image Classification via Prediction Score Decomposition

PDF: http://www.eccv2016.org/files/posters/P-4A-26.pdf

Duy-Dinh Le, National Institute of Informat:

Tien-Dung Mai, University of Information Technology:

Shin’ichi Satoh, National Institute of Informatics, Japan:

Thanh Duc Ngo, University of Information Technology:

Duc Anh Duong, University of Information Technology:

【Scene recognition】P-4B-36.   Visualizing Image Priors

PDF: http://www.eccv2016.org/files/posters/P-4B-36.pdf

Tamar Shaham, Technion:

Tomer Michaeli, Technion:

【Text recognition】P-3B-44.   Detecting Text in Natural Image with Connectionist Text Proposal Network

PDF: http://www.eccv2016.org/files/posters/P-3B-44.pdf

Zhi Tian, SIAT:

Weilin Huang, The University of Oxford:

Tong He, Wuhan University:

Pan He, SIAT,MMLAB:

Yu Qiao, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences:

【Image retrieval】O-1A-01.   CNN Image Retrieval Learns from Bo W: Unsupervised Fine-Tuning with Hard Examples

PDF: http://www.eccv2016.org/files/posters/O-1A-01.pdf

Filip Radenovic, CMP, CVUT:

Giorgos Tolias, CMP, CVUT:

Ondra Chum, CMP, CVUT:

【Image retrieval】O-1A-01.   CNN Image Retrieval Learns from Bo W: Unsupervised Fine-Tuning with Hard Examples

PDF: http://www.eccv2016.org/files/posters/O-1A-01.pdf

Filip Radenovic, CMP, CVUT:

Giorgos Tolias, CMP, CVUT:

Ondra Chum, CMP, CVUT:

【Image retrieval】P-1A-46.   Matching Handwritten Document Images

PDF: http://www.eccv2016.org/files/posters/P-1A-46.pdf

Praveen Krishnan, IIIT H:

C.V. Jawahar, IIIT Hyderabad:

【Image retrieval】P-1B-21.   Leveraging Visual Question Answering for Image-Caption Ranking

PDF: http://www.eccv2016.org/files/posters/P-1B-21.pdf

Xiao Lin, Virginia Tech:

Devi Parikh, Virginia Tech: https://filebox.ece.vt.edu/~parikh/

【Image retrieval】P-1B-25.   Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding

PDF: http://www.eccv2016.org/files/posters/P-1B-25.pdf

Ioannis Chiotellis, TUM:

Rudolph Triebel, TU Munich:

Thomas Windheuser, TU Muenchen:

Daniel Cremers: http://vision.in.tum.de/

【Image retrieval】D-1B-48. Object Detection and Retrieval using Natural Langua

Ronghang Hu, UC, Berkeley and ICSI:

Xing Chao Peng, Boston University:

Tao Zhou, Canon USA Innovation Center:

Jie Yu, Canon USA Innovation Center:

Sandra Skaff, Canon USA Innovation Center:

Trevor Darrell, UC, Berkeley and ICSI: http://www.eecs.berkeley.edu/~trevor/

Kate Saenko, Boston University:

【Image retrieval】O-2A-04. Fast Global Registrati

Qian-Yi Zhou, Intel Labs:

Jaesik Park, Intel Labs:

Vladlen Koltun, Intel Labs: http://vladlen.info/publications/

【Image retrieval】S-2A-06.   Binary Hashing with Semidefinite Relaxation and Augmented Lagrangian

PDF: http://www.eccv2016.org/files/posters/S-2A-06.pdf

Thanh-Toan Do, SUTD:

Dung Doan, SUTD:

Duc-Thanh Nguyen, University of Wollongong:

Ngai-Man Cheung, SUTD:

【Image retrieval】P-2A-47.   Pose Hashing with Microlens Arrays

PDF: http://www.eccv2016.org/files/posters/P-2A-47.pdf

Ian Schillebeeckx, Washington University in St. L:

Robert Pless, Washington University in St. Louis:

【Image retrieval】P-3A-44.   Network flow formulations for Learning Binary Hashing

PDF: http://www.eccv2016.org/files/posters/P-3A-44.pdf

Lopamudra Mukherjee, University of Wisc Whitewater:

Jiming Peng, University of Houston:

Trevor Sigmund, Univ of Wisconsin Whitewater:

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

【Image retrieval】P-3B-15.   Kernel-Based Supervised Discrete Hashing for Image Retrieval

PDF: http://www.eccv2016.org/files/posters/P-3B-15.pdf

Xiaoshuang Shi, University of Florida:

Fuyong Xing, University of Florida:

Jinzheng Cai, University of Florida:

Zizhao Zhang, University of Florida:

Yuanpu Xie, University of Florida:

Lin Yang, University of Florida:

【Image retrieval】P-3B-30.   Approximate search with quantized sparse representations

PDF: http://www.eccv2016.org/files/posters/P-3B-30.pdf

Himalaya Jain, Inria:

Patrick Perez, Technicolor, France:

Rémi Gribonval,:

joaquin Zepeda, Technicolor:

Hervé Jegou,:

【Image retrieval】P-3B-35.   Video Summarization with Long Short-term Memory

PDF: http://www.eccv2016.org/files/posters/P-3B-35.pdf

Ke Zhang, USC:

Wei-Lun Chao, USC:

Fei Sha, UCLA:

Kristen Grauman, University of Texas at Austin: http://www.cs.utexas.edu/~grauman/

【Image retrieval】P-3B-41.   Query-Focused Extractive Video Summarization

PDF: http://www.eccv2016.org/files/posters/P-3B-41.pdf

Aidean Sharghi Karganroodi, University of Central Florida:

Boqing Gong, University of Central Florida:

Mubarak Shah, University of Central Florida: http://crcv.ucf.edu/people/faculty/shah.html

【Image retrieval】P-4A-25.   End-to-End Localization and Ranking for Relative Attributes

PDF: http://www.eccv2016.org/files/posters/P-4A-25.pdf

Krishna Kumar Singh, UC Davis:

Yong Jae Lee, UC Davis:

【Image retrieval】P-4B-42.   Deep Image Retrieval: Learning Global Representations for Image Search

PDF: http://www.eccv2016.org/files/posters/P-4B-42.pdf

Albert Gordo, Xerox Research:

Jon Almazan, XRCE:

Jerome Revaud, Xerox Research: http://lear.inrialpes.fr/people/revaud/

Diane Larlus, Xerox:

【3D modeling】P-1A-12.   Deep Learning the City: Quantifying Urban Perception At A Global Scale

PDF: http://www.eccv2016.org/files/posters/P-1A-12.pdf

Abhimanyu Dubey,:

Nikhil Naik, MIT:

Devi Parikh, Virginia Tech: https://filebox.ece.vt.edu/~parikh/

Ramesh Raskar, MIT Media Lab:

Cesar Hidalgo, MIT:

【3D modeling】P-1A-34.   Rep Match: Robust Feature Matching and Pose for Reconstructing Modern Cities

PDF: http://www.eccv2016.org/files/posters/P-1A-34.pdf

Wen-Yan Lin, ADSC:

Siying Liu, UIUC:

Nianjuan Jiang, Advanced Digital Sciences Center (ADSC):

Minh Do, University of Illinois at Urbana-Champaign:

ping tan,:

Jiangbo Lu, ADSC Singapore:

【3D modeling】P-1A-41.   SDF-2-SDF: Highly Accurate 3D Object Reconstruction

PDF: http://www.eccv2016.org/files/posters/P-1A-41.pdf

Miroslava Slavcheva, Siemens AG:

Wadim Kehl, TU München:

Nassir Navab,: http://campar.in.tum.de/Main/NassirNavab

Slobodan Ilic, TUM:

【3D modeling】P-2A-21.   On Shape Reconstruction from Implicit Forms

PDF: http://www.eccv2016.org/files/posters/P-2A-21.pdf

Li Wang, Inria:

Franck Hétroy-Wheeler, University Grenoble Alpes:

Edmond Boyer, Inria:

【3D modeling】P-2A-28.   Indoor-Outdoor 3D Reconstruction Alignment

PDF: http://www.eccv2016.org/files/posters/P-2A-28.pdf

Andrea Cohen, ETHZ:

Johannes Schönberger, ETH Zürich:

Pablo Speciale, ETHZ:

Torsten Sattler, ETH Zurich:

Jan-Michael Frahm,:

Marc Pollefeys, ETH: http://www.inf.ethz.ch/personal/pomarc/

【3D modeling】P-2A-40.   Fine-Scale Surface Normal Estimation using a Single NIR Image

PDF: http://www.eccv2016.org/files/posters/P-2A-40.pdf

Youngjin Yoon, KAIST:

Gyeongmin Choe, KAIST:

Namil Kim, KAIST:

Joon-Young Lee, Adobe:

In So Kweon, KAIST: http://rcv.kaist.ac.kr/

【3D modeling】P-2B-18.   Marker-less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps

PDF: http://www.eccv2016.org/files/posters/P-2B-18.pdf

Yu Du,:

Yongkang Wong,:

Yonghao Liu,:

Feilin Han, Zhejiang University:

Yilin Gui,:

Zhen Wang,:

Mohan Kankanhalli, National University of Singapore:

Weidong Geng:

【3D modeling】P-2B-20.   Manhattan-world Urban Reconstruction from Point Clouds

PDF: http://www.eccv2016.org/files/posters/P-2B-20.pdf

Minglei Li, Nanjing University of Aeronautics and Astronautics:

Peter Wonka,:

Liangliang Nan, KAUST:

【3D modeling】P-2B-23.   Can we Jointly Register and Reconstruct Creased Surfaces by Shape-from-Template Accurately?

PDF: http://www.eccv2016.org/files/posters/P-2B-23.pdf

Mathias Gallardo, ISIT, UMR 6284 CNRS/Ud A:

Toby Collins, Universite d’Auvergne:

Adrien Bartoli, Universite d’Auvergne:

【3D modeling】P-2B-36.   Generative Image Modeling using Style and Structure Adversarial Networks

PDF: http://www.eccv2016.org/files/posters/P-2B-36.pdf

Xiaolong Wang, CMU:

Abhinav Gupta: http://www.cs.cmu.edu/~abhinavg/

【3D modeling】D-2B-48. Mobile AR for Dentistry: Virtual Try-On in Live

Gábor Sörös, Kapanu AG and ETH Zurich:

Marcel Lancelle, Kapanu AG and ETH Zurich:

Nicolas Degen, Kapanu AG and ETH Zurich:

Roland Mörzinger, Kapanu AG and ETH Zurich:

【3D modeling】P-3A-17.   Modeling Context Between Objects for Referring Expression Understanding

PDF: http://www.eccv2016.org/files/posters/P-3A-17.pdf

Varun Nagaraja, University of Maryland:

Vlad Morariu, University of Maryland:

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

【3D modeling】P-3A-27.   Towards large-scale city reconstruction from satellites

PDF: http://www.eccv2016.org/files/posters/P-3A-27.pdf

liuyun Duan,:

Florent Lafarge:

【3D modeling】S-3C-09.   Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees

PDF: http://www.eccv2016.org/files/posters/S-3C-09.pdf

Kyle Simek, University of Arizona:

Ravishankar Palanivelu, University of Arizona:

Kobus Barnard, University of Arizona:

【3D modeling】S-3B-09.   Multi-view 3D Models from Single Images With a Convolutional Network

PDF: http://www.eccv2016.org/files/posters/S-3B-09.pdf

Maxim Tatarchenko, University of Freiburg:

Alexey Dosovitskiy, University of Freiburg:

Thomas Brox: http://lmb.informatik.uni-freiburg.de/people/brox/index.en.html

【3D modeling】P-3B-25.   Pseudo-Geometric Formulation for Fitting Equidistant Parallel Lines

PDF: http://www.eccv2016.org/files/posters/P-3B-25.pdf

FAISAL AZHAR, HP Labs:

STEPHEN POLLARD, HP Labs.:

【3D modeling】P-3B-28.   Template-free 3D Reconstruction of Poorly-textured Nonrigid Surfaces

PDF: http://www.eccv2016.org/files/posters/P-3B-28.pdf

Xuan Wang, Xi’an Jiaotong University:

Mathieu Salzmann, EPFL:

Fei Wang, Xi’an Jiaotong University:

Jizhong Zhao, Xi’an Jiaotong university:

【3D modeling】S-3C-08.   Object Net3D: A Large Scale Database for 3D Object Recognition

PDF: http://www.eccv2016.org/files/posters/S-3C-08.pdf

Yu Xiang, University of Michigan:

Wonhui Kim, University of Michigan:

Wei Chen, Stanford University:

Jingwei Ji, Stanford University:

Christopher Choy, Stanford University:

Hao Su, Stanford:

Roozbeh Mottaghi, Allen Institute for AI: http://www.cs.stanford.edu/~roozbeh/

Leonidas J. Guibas,:

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【3D modeling】S-3C-09.   Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees

PDF: http://www.eccv2016.org/files/posters/S-3C-09.pdf

Kyle Simek, University of Arizona:

Ravishankar Palanivelu, University of Arizona:

Kobus Barnard, University of Arizona:

【3D modeling】P-3C-16.   Deep Markov Random Field for Image Modeling

PDF: http://www.eccv2016.org/files/posters/P-3C-16.pdf

Zhirong Wu, The Chinese University of Hong Kong:

Dahua Lin, CUHK: http://dahua.me/

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

【3D modeling】P-3C-17.   A Symmetry Prior for Convex Variational 3D Reconstruction

PDF: http://www.eccv2016.org/files/posters/P-3C-17.pdf

Pablo Speciale, ETHZ:

Martin R. Oswald, ETH Zurich:

Andrea Cohen, ETHZ:

Marc Pollefeys, ETH: http://www.inf.ethz.ch/personal/pomarc/

【3D modeling】P-3C-20.   Volume Deform: Real-time Volumetric Non-rigid Reconstruction

PDF: http://www.eccv2016.org/files/posters/P-3C-20.pdf

Matthias Innmann, University Erlangen-Nuremberg:

Michael Zollhoefer, MPI Informatics:

Matthias Niessner, Stanford University:

Christian Theobalt, MPI Informatics:

Marc Stamminger, University of Erlangen-Nuremberg:

【3D modeling】P-3C-21.   Match: Monocular v SLAM and Piecewise Planar Reconstruction using Fast Plane Correspondences

PDF: http://www.eccv2016.org/files/posters/P-3C-21.pdf

Carolina Raposo, University of Coimbra:

Joao Barreto, Universidade de Coimbra:

【3D modeling】P-3C-28.   Real-time Large-Scale Dense 3D Reconstruction with Loop Closure

PDF: http://www.eccv2016.org/files/posters/P-3C-28.pdf

Olaf Kahler, University of Oxford:

David Murray, Oxford: http://www.robots.ox.ac.uk/~lav/

Victor Prisacariu, Oxford:

【3D modeling】P-3C-36.   3D-R2N2: A unified approach for single and multi-view 3D object reconstruction

PDF: http://www.eccv2016.org/files/posters/P-3C-36.pdf

Christopher Choy, Stanford University:

Danfei Xu, Stanford University:

Jun Young Gwak, Stanford:

Kevin Chen, Stanford University:

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【3D modeling】D-3C-49. From Low- to High-Quality Depth Sensors for 3D Object Reconstruction with SDF-2-SD

Miroslava Slavcheva, Technische Universität München and Siemens AG:

Wadim Kehl, Technische Universität München:

Nassir Navab, Technische Universität München: http://campar.in.tum.de/Main/NassirNavab

Slobodan Ilic, Technische Universität München and Siemens AG:

【3D modeling】O-4A-01.   Real-Time 3D Reconstruction and 6-Do F Tracking with an Event Camera

PDF: http://www.eccv2016.org/files/posters/O-4A-01.pdf

Hanme Kim, Imperial College London:

Stefan Leutenegger, Imperial College London:

Andrew Davison:

【3D modeling】O-4A-02.   Single Image 3D Interpreter Network

PDF: http://www.eccv2016.org/files/posters/O-4A-02.pdf

Jiajun Wu, MIT:

Tianfan Xue, MIT:

Joseph Lim, MIT:

Yuandong Tian, FAIR:

Joshua Tenenbaum, MIT:

Antonio Torralba,: http://web.mit.edu/torralba/www/

William Freeman: http://people.csail.mit.edu/billf/

【3D modeling】P-4A-10.   House Craft: Building Houses from Rental Ads and Street Views

PDF: http://www.eccv2016.org/files/posters/P-4A-10.pdf

Hang Chu, University of Toronto:

Shenlong Wang, University of Toronto:

Raquel Urtasun,: http://www.cs.toronto.edu/~urtasun/

Sanja Fidler, University of Toronto:

【3D modeling】P-4A-20.   Semantic 3D Reconstruction of Heads

PDF: http://www.eccv2016.org/files/posters/P-4A-20.pdf

Fabio Maninchedda, ETH Zürich:

Christian Haene, ETH Zurich:

Bastien Jacquet, ETH Zürich:

Amael Delaunoy,:

Marc Pollefeys, ETH: http://www.inf.ethz.ch/personal/pomarc/

【3D modeling】P-4A-46.   Sy B3R: A Realistic Synthetic Benchmark for 3D Reconstruction from Images

PDF: http://www.eccv2016.org/files/posters/P-4A-46.pdf

Andreas Ley, Technische Universität Berlin:

Ronny Hänsch, Technische Universität Berlin:

Olaf Hellwich, Technische Universität Berlin:

【3D modeling】P-4B-21.   Head Reconstruction from Internet Photos

PDF: http://www.eccv2016.org/files/posters/P-4B-21.pdf

Shu Liang,:

Linda Shapiro, University of Washington: http://homes.cs.washington.edu/~shapiro/

Ira Kemelmacher, University of Washington:

【3D modeling】P-4B-28.   Spatio-Temporally Consistent Correspondence for Dense Dynamic Scene Modeling

PDF: http://www.eccv2016.org/files/posters/P-4B-28.pdf

Dinghuang Ji, UNC:

Enrique Dunn, UNC Chapel Hill:

Jan-Michael Frahm:

【3D modeling】P-4B-29.   3D Image Reconstruction from X-Ray Measurements with Overlap

PDF: http://www.eccv2016.org/files/posters/P-4B-29.pdf

Maria Klodt, University of Oxford:

Raphael Hauser, University of Oxford:

【3D modeling】P-4B-43.   Building Scene Models by Completing and Hallucinating Depth and Semantics

PDF: http://www.eccv2016.org/files/posters/P-4B-43.pdf

Miaomiao Liu, Data61, CSIRO, (NICTA):

Xuming He, NICTA: http://users.cecs.anu.edu.au/~hexm/

Mathieu Salzmann, EPFL:

【Feature matching】P-1A-15. Learnable Histogram: Statistical Context Features for Deep Neural Networks

Zhe Wang, CUHK:

Hongsheng Li, CUHK:

Wanli Ouyang, Chinese University of Hong Kong: http://www.ee.cuhk.edu.hk/~wlouyang/

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

【Feature matching】P-2A-15.   Evaluation of LBP and Deep Texture Descriptors with A New Robustness Benchmark

PDF: http://www.eccv2016.org/files/posters/P-2A-15.pdf

Li Liu, NUDT:

Paul Fieguth,:

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

Matti Pietikainen, University of Oulu:

Dewen Hu:

【Feature matching】P-2B-14. Going Further with Point Pair Featur

Stefan Hinterstoisser, Google:

Vincent Lepetit,: http://cvlabwww.epfl.ch/~lepetit/

Kurt Konolige, Google:

Naresh Rajkumar, Google:

【Feature matching】S-4A-08.   LIFT: Learned Invariant Feature Transform

PDF: http://www.eccv2016.org/files/posters/S-4A-08.pdf

Kwang Yi, EPFL:

Eduard Trulls, EPFL:

Vincent Lepetit,: http://cvlabwww.epfl.ch/~lepetit/

Pascal Fua,: http://cvlabwww.epfl.ch/~fua/

【Pose estimation】P-1A-24.   Fast 6D Pose Estimation from a Monocular Image using Hierarchical Pose Trees

PDF: http://www.eccv2016.org/files/posters/P-1A-24.pdf

Yoshinori Konishi, OMRON Corporation:

Yuki Hanzawa, OMRON Corporation:

Masato Kawade, OMRON Corporation:

Manabu Hashimoto, Chukyo University:

【Pose estimation】P-1A-29.   Projective Bundle Adjustment from Arbitrary Initialization using the Variable Projection Method

PDF: http://www.eccv2016.org/files/posters/P-1A-29.pdf

Je Hyeong Hong, University of Cambridge:

Christopher Zach, Toshiba Research Europe:

Andrew Fitzgibbon, Microsoft Research:

Roberto Cipolla: http://mi.eng.cam.ac.uk/~cipolla/index.htm

【Pose estimation】P-1A-42.   Knowledge transfer for scene-specific motion prediction

PDF: http://www.eccv2016.org/files/posters/P-1A-42.pdf

Lamberto Ballan, Stanford University:

Francesco Castaldo, Seconda Università di Napoli:

Alexandre Alahi, Stanford University:

Francesco Palmieri, Seconda Università di Napoli:

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【Pose estimation】P-1A-43.   Weakly Supervised Localization using Deep Feature Maps

PDF: http://www.eccv2016.org/files/posters/P-1A-43.pdf

Archith Bency, UCSB:

Heesung Kwon, US Army Research Laboratory:

Hyungtae Lee, US Army Research Laboratory:

Karthikeyan Shanmuga Vadivel, Synaptics:

B.S. Manjunath, UCSB:

【Pose estimation】P-1B-30.   Symmetric Non-Rigid Structure from Motion for Category-Specific Object Structure Estimation

PDF: http://www.eccv2016.org/files/posters/P-1B-30.pdf

Yuan Gao, City University of Hong Kong:

Alan Yuille, UCLA: http://www.stat.ucla.edu/~yuille/

【Pose estimation】P-2A-14.   Structure from motion on a sphere

PDF: http://www.eccv2016.org/files/posters/P-2A-14.pdf

Jonathan Ventura, University of Colorado Colorad:

【Pose estimation】P-2A-19.   Graph-Based Consistent Matching for Structure-from-Motion

PDF: http://www.eccv2016.org/files/posters/P-2A-19.pdf

Tianwei Shen, HKUST:

Siyu Zhu, HKUST:

Tian Fang, HKUST:

Runze Zhang, HKUST:

Long Quan, The Hong Kong University of Science and Technology: http://visgraph.cs.ust.hk/index.html

【Pose estimation】P-2A-23.   Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation

PDF: http://www.eccv2016.org/files/posters/P-2A-23.pdf

Wadim Kehl, TU München:

Fausto Milletari, Technische Universität München:

Federico Tombari, University of Bologna: http://vision.deis.unibo.it/fede/

Slobodan Ilic, TUM:

Nassir Navab: http://campar.in.tum.de/Main/NassirNavab

【Pose estimation】P-2A-43.   Generic 3D Representation via Pose Estimation and Matching

PDF: http://www.eccv2016.org/files/posters/P-2A-43.pdf

Amir Zamir, Stanford University:

Pulkit Agrawal, UC Berkeley:

Silvio Savarese,: http://cvgl.stanford.edu/silvio/

Tilman Wekel, Stanford University:

Colin Wei, Stanford University:

Jitendra Malik, UC Berkeley: http://www.cs.berkeley.edu/~malik/

【Pose estimation】D-2A-49. Realtime Multi­person Pose Estimatio

Zhe Cao, Carnegie Mellon University:

Shih­En Wei, Carnegie Mellon University:

Tomas Simon, Carnegie Mellon University:

Yaser Sheikh, Carnegie Mellon University: http://www.cs.cmu.edu/~yaser/

【Pose estimation】P-3A-24.   Degeneracies in Rolling Shutter Sf M

PDF: http://www.eccv2016.org/files/posters/P-3A-24.pdf

Cenek Albl, Czech Technical University:

Akihiro Sugimoto, NII:

Tomas Pajdla:

【Pose estimation】P-3A-28.   Weakly Supervised Object Localization Using Size Estimates

PDF: http://www.eccv2016.org/files/posters/P-3A-28.pdf

Miaojing SHI, University of Edinburgh:

Vittorio Ferrari: http://groups.inf.ed.ac.uk/calvin/index.html

【Pose estimation】P-3A-32.   A Minimal Solution for Non-Perspective Pose Estimation from Line Correspondences

PDF: http://www.eccv2016.org/files/posters/P-3A-32.pdf

Gim Hee Lee, NUS:

【Pose estimation】P-3A-34.   Minimal Solvers for Generalized Pose and Scale Estimation from Two Rays and One Point

PDF: http://www.eccv2016.org/files/posters/P-3A-34.pdf

Federico Camposeco, ETHZ:

Torsten Sattler, ETH Zurich:

Marc Pollefeys, ETH: http://www.inf.ethz.ch/personal/pomarc/

【Pose estimation】S-3B-05.   When is Rotations Averaging Hard?

PDF: http://www.eccv2016.org/files/posters/S-3B-05.pdf

Kyle Wilson, Washington College:

David Bindel, Cornell University:

Noah Snavely:

【Pose estimation】S-3B-07.   Shape Fit and Shape Kick for Robust, Scalable Structure from Motion

PDF: http://www.eccv2016.org/files/posters/S-3B-07.pdf

Tom Goldstein, University of Maryland, College Park:

Paul Hand,:

Vladislav Voroninski, MIT:

Stefano Soatto, University of California, Los Angeles: http://vision.ucla.edu/projects.html

Choongbum Lee:

【Pose estimation】P-3B-24.   Accurate and Linear Time Pose Estimation from Points and Lines

PDF: http://www.eccv2016.org/files/posters/P-3B-24.pdf

Alexander Vakhitov, SPb SU:

Jan Funke, Institut de Robòtica i Informà:

Francesc Moreno-Noguer, Institut de Robotica i Informatica Industrial (UPC/CSIC):

【Pose estimation】P-3B-37.   Robust and Accurate Line- and/or Point-Based Pose Estimation without Manhattan Assumptions

PDF: http://www.eccv2016.org/files/posters/P-3B-37.pdf

Yohann Salaun, LIGM-Imagine:

Renaud Marlet,:

Pascal Monasse, Universite Paris-Est:

【Pose estimation】P-3B-43.   Pla Net – Photo Geolocation with Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3B-43.pdf

Tobias Weyand, Google:

Ilya Kostrikov, RWTH Aachen University:

James Philbin, Zoox:

【Pose estimation】D-3B-48. RGB-D SLAM with fast and robust relocalization and HDR texture mapping

Shuda Li, University of Bristol:

Andrew Calway, University of Bristol:

【Pose estimation】P-3C-32.   Bayesian Image based 3D Pose Estimation

PDF: http://www.eccv2016.org/files/posters/P-3C-32.pdf

Valsamis Ntouskos, Sapienza University of Rome:

Fiora Pirri, University of Rome, Sapienza:

Marta Sanzari, Sapienza:

【Pose estimation】P-4A-40.   Pose Estimation Errors, the Ultimate Diagnosis

PDF: http://www.eccv2016.org/files/posters/P-4A-40.pdf

Carolina Redondo-Cabrera, University of Alcalá:

Roberto Lopez-Sastre, University of Alcala:

Yu Xiang,:

Tinne Tuytelaars, KU Leuven: http://homes.esat.kuleuven.be/~tuytelaa/

Silvio Savarese: http://cvgl.stanford.edu/silvio/

【Pose estimation】P-4A-42.   Integration of Probabilistic Pose Estimates From Multiple Views

PDF: http://www.eccv2016.org/files/posters/P-4A-42.pdf

Ozgur Erkent, Innsbruck University:

Dadhichi Shukla,:

Justus Piater, University of Innsbruck:

【Stereo matching】P-1A-28.   Scene depth profiling using Helmholtz Stereopsis

PDF: http://www.eccv2016.org/files/posters/P-1A-28.pdf

Hironori Mori, Sony Deutschland Gmb H:

Roderick Koehle,:

Markus Kamm,:

【Stereo matching】P-1B-15.   Photometric Stereo under Non-uniform Light Intensities and Exposures

PDF: http://www.eccv2016.org/files/posters/P-1B-15.pdf

Donghyeon Cho, KAIST:

Yasuyuki Matsushita,:

Yu-Wing Tai, Korea Advanced Institute of Science and Technology:

In So Kweon, KAIST: http://rcv.kaist.ac.kr/

【Stereo matching】P-1B-33.   Coarse-to-fine Planar Regularization for Dense Monocular Depth Estimation

PDF: http://www.eccv2016.org/files/posters/P-1B-33.pdf

Stephan Liwicki,:

Christopher Zach, Toshiba Research Europe:

Ondrej Miksik, University of Oxford:

Philip Torr, Oxford University: http://www.robots.ox.ac.uk/~tvg/

【Stereo matching】P-2A-39.   Shading-aware Multi-view Stereo

PDF: http://www.eccv2016.org/files/posters/P-2A-39.pdf

Fabian Langguth, TU Darmstadt:

Kalyan Sunkavalli, Adobe Systems Inc.:

Sunil Hadap,:

Michael Goesele, TU Darmstadt:

【Stereo matching】P-2A-41.   Pixelwise View Selection for Unstructured Multi-View Stereo

PDF: http://www.eccv2016.org/files/posters/P-2A-41.pdf

Johannes Schönberger, ETH Zürich:

Enliang Zheng, UNC Chapel Hill:

Marc Pollefeys, ETH: http://www.inf.ethz.ch/personal/pomarc/

Jan-Michael Frahm:

【Stereo matching】S-2B-07.   Fast Guided Global Interpolation for Depth and Motion

PDF: http://www.eccv2016.org/files/posters/S-2B-07.pdf

Yu Li, Advanced Digital Sci. Center:

Dongbo Min, Chungnam National University:

Minh Do, University of Illinois at Urbana-Champaign:

Jiangbo Lu, ADSC Singapore:

【Stereo matching】O-2B-04.   Focal flow: Measuring depth and velocity from defocus and differential motion

PDF: http://www.eccv2016.org/files/posters/O-2B-04.pdf

Emma Alexander, Harvard University:

Qi Guo, Harvard University:

Sanjeev Koppal, University of Florida:

Steven Gortler: http://gvi.seas.harvard.edu/

Todd Zickler:

【Stereo matching】S-2B-07.   Fast Guided Global Interpolation for Depth and Motion

PDF: http://www.eccv2016.org/files/posters/S-2B-07.pdf

Yu Li, Advanced Digital Sci. Center:

Dongbo Min, Chungnam National University:

Minh Do, University of Illinois at Urbana-Champaign:

Jiangbo Lu, ADSC Singapore:

【Stereo matching】P-3A-20.   Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3A-20.pdf

Junyuan Xie, University of Washington:

Ross Girshick,: http://www.cs.berkeley.edu/~rbg/

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

【Stereo matching】S-3C-05.   Linear depth estimation from an uncalibrated, monocular polarisation image

PDF: http://www.eccv2016.org/files/posters/S-3C-05.pdf

William Smith, University of York:

Ravi Ramamoorthi,:

Silvia Tozza:

【Stereo matching】S-3C-07.   Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural Fields

PDF: http://www.eccv2016.org/files/posters/S-3C-07.pdf

Seungryong Kim, Yonsei University:

Kihong Park, Yonsei Univ.:

Kwanghoon Sohn, Yonsei university:

Stephen Lin, Microsoft Research Asia, China:

【Stereo matching】S-3C-05.   Linear depth estimation from an uncalibrated, monocular polarisation image

PDF: http://www.eccv2016.org/files/posters/S-3C-05.pdf

William Smith, University of York:

Ravi Ramamoorthi,:

Silvia Tozza:

【Stereo matching】P-3C-22.   Peripheral Expansion of Depth Information via Layout Estimation with Fisheye Camera

PDF: http://www.eccv2016.org/files/posters/P-3C-22.pdf

Alejandro Perez-Yus, Universidad de Zaragoza:

Gonzalo Lopez-Nicolas, Universidad de Zaragoza:

Josechu Guerrero, Universidad de Zaragoza:

【Stereo matching】P-3C-43. Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

Ravi Garg, University of Adelaide:

Vijay Kumar, University of Adelaide:

Gustavo Carneiro, University of Adelaide: http://cs.adelaide.edu.au/~carneiro/research.html

Ian Reid, University of Adelaide: http://www.robots.ox.ac.uk/~ian/

【Stereo matching】P-4A-18.   Shape from Water: Bispectral Light Absorption for Depth Recovery

PDF: http://www.eccv2016.org/files/posters/P-4A-18.pdf

Yuta Asano,:

Yinqiang Zheng, National Institute of Informatics, Japan:

Ko Nishino, Drexel University:

Imari Sato, National Institute of Informatics, Japan:

【Stereo matching】P-4B-26.   Search-based Depth Estimation via Coupled Dictionary Learning with Large-Margin Structure Inference

PDF: http://www.eccv2016.org/files/posters/P-4B-26.pdf

Yan Zhang, HIT:

Rongrong Ji, Xiamen University:

Xiaopeng Fan,:

Yan Wang, Microsoft:

Feng Guo, Xiamen University:

Yue Gao,:

debin Zhao:

【Optical flow】P-2B-45.   Fast Optical Flow using Dense Inverse Search

PDF: http://www.eccv2016.org/files/posters/P-2B-45.pdf

Till Kroeger, ETH Zuerich:

Radu Timofte, ETH Zurich:

Dengxin Dai, ETH Zurich:

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

【Optical flow】S-3C-06.   Online Variational Bayesian Motion Averaging

PDF: http://www.eccv2016.org/files/posters/S-3C-06.pdf

Guillaume Bourmaud, Toshiba CRL:

【Optical flow】P-3C-44.   A Continuous Optimization Approach for Efficient and Accurate Scene Flow

PDF: http://www.eccv2016.org/files/posters/P-3C-44.pdf

Zhaoyang Lv, Georgia Tech:

Chris Beall, Georgia Tech:

Pablo Alcantarilla, i Robot Corporation:

Fuxin Li, Oregon State University: http://www.cc.gatech.edu/~fli/

Zsolt Kira, Georgia Tech Research Institute:

Frank Dellaert:

【Optical flow】P-4A-39.   Guided Matching based on Statistical Optical Flow for Fast and Robust Correspondence Analysis

PDF: http://www.eccv2016.org/files/posters/P-4A-39.pdf

Josef Maier, AIT Austrian Institute of Technology:

Martin Humenberger, AIT Austrian Institute of Technology:

Markus Murschitz, AIT Austrian Institute of Technology:

Oliver Zendel, AIT Austrian Institute of Technology:

Markus Vincze, TU Wien:

【Optical flow】P-4B-22.   The Conditional Lucas & Kanade Algorithm

PDF: http://www.eccv2016.org/files/posters/P-4B-22.pdf

Chen-Hsuan Lin, Carnegie Mellon University:

Rui Zhu, Carnegie Mellon University:

Simon Lucey, CMU:

【Optical flow】P-4B-34.   Temporally Robust Global Motion Compensation by Keypoint-based Congealing

PDF: http://www.eccv2016.org/files/posters/P-4B-34.pdf

Seyed Morteza Safdarnejad, Michigan State University:

Yousef Atoum, Michigan State University:

Xiaoming Liu, Michigan State University:

【Optical flow】P-4B-37.   Exploiting Semantic Information and Deep Matching for Optical Flow

PDF: http://www.eccv2016.org/files/posters/P-4B-37.pdf

Min Bai, University of Toronto:

Wenjie Luo, University of Toronto:

Kaustav Kundu, University of Toronto:

Raquel Urtasun: http://www.cs.toronto.edu/~urtasun/

【Region matching】P-1A-13.   4D Match Trees for Non-rigid Surface Alignment

PDF: http://www.eccv2016.org/files/posters/P-1A-13.pdf

Armin Mustafa, University of Surrey:

Hansung Kim, U.Surrey:

Adrian Hilton, University of Surrey:

【Region matching】P-2B-46.   Global Registration of 3D Point Sets via LRS decomposition

PDF: http://www.eccv2016.org/files/posters/P-2B-46.pdf

Federica Arrigoni, University of Udine:

Beatrice Rossi, AST:

Andrea Fusiello, University of Udine:

【Region matching】P-3C-14.   Learning Temporal Transformations From Time-Lapse Videos

PDF: http://www.eccv2016.org/files/posters/P-3C-14.pdf

Yipin Zhou, UNC:

Tamara Berg, University on North Carolina:

【Region matching】P-3C-34.   Novel Coplanar Line-points Invariants for Robust Line Matching Across Views

PDF: http://www.eccv2016.org/files/posters/P-3C-34.pdf

Qi Jia, Dalian university of technology:

Xinkai Gao, Dalian university of technolgy:

Xin Fan, Dalian University of Technolog:

Zhongxuan Luo, Dalian university of technology:

Haojie Li, Dalian university of technology:

Ziyao Chen, Dalian university of technology:

【Region matching】P-3C-39.   Deep Self-Correlation Descriptor for Dense Cross-Modal Correspondence

PDF: http://www.eccv2016.org/files/posters/P-3C-39.pdf

Seungryong Kim, Yonsei University:

Dongbo Min, Chungnam National University:

Stephen Lin, Microsoft Research Asia, China:

Kwanghoon Sohn, Yonsei university:

【Region matching】P-3C-40.   Structured Matching for Phrase Localization

PDF: http://www.eccv2016.org/files/posters/P-3C-40.pdf

Mingzhe Wang, University of Michgan:

Mahmoud Azab, University of Michigan:

Noriyuki Kojima, University of Michigan:

Rada Mihalcea, University of Michigan:

Jia Deng, University of Michigan:

【Region matching】O-4A-04.   Shape acquisition and registration for 3D endoscope based on grid pattern projection

PDF: http://www.eccv2016.org/files/posters/O-4A-04.pdf

Ryo Furukawa, Hiroshima City University:

Hiroki Morinaga, Kagoshima Univeristy:

Yoji Sanomura, Hiroshima University:

Shinji Tanaka, Hiroshima University:

Shigeto Yoshida, Hiroshima General Hospital of West Japan Railway Company:

Hiroshi Kawasaki, Kagoshima University:

【Region matching】P-4B-16. Interpreting the Ratio Criterion for Matching SIFT Descriptors

Avi Kaplan, Technion, Israel:

Tamar Avraham, Technion:

Michael Lindenbaum, Technion:

【Region matching】P-4B-31.   Resonant Deformable Matching: Simultaneous Registration and Reconstruction

PDF: http://www.eccv2016.org/files/posters/P-4B-31.pdf

John Corring, University of Florida:

Anand Rangarajan, University of Florida:

【Region matching】P-4B-38.   Similarity Registration Problems for 2D/3D Ultrasound Calibration

PDF: http://www.eccv2016.org/files/posters/P-4B-38.pdf

Francisco Vasconcelos, UCL:

Sebastien Ourselin,:

Donald Peebles,:

Danail Stoyanov:

【Image editing】P-2A-24.   A Neural Approach to Blind Motion Deblurring

PDF: http://www.eccv2016.org/files/posters/P-2A-24.pdf

Ayan Chakrabarti, TTI-Chicago:

【Image editing】P-2A-27.   ATGV-Net: Accurate Depth Super-Resolution

PDF: http://www.eccv2016.org/files/posters/P-2A-27.pdf

Gernot Riegler, Graz University of Technology:

Matthias Rüther, Graz University of Technology:

Horst Bischof, Graz University of Technology: http://www.icg.tugraz.at/Members/bischof

【Image editing】P-2A-32.   Depth Map Super Resolution by Deep Multi-Scale Guidance

PDF: http://www.eccv2016.org/files/posters/P-2A-32.pdf

Tak-Wai Hui, The Chinese University of HK:

Chen-Change Loy, the Chinese University of Hong Kong:

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

【Image editing】P-2A-33. SEAGULL: Seam-guided Local Alignment for Parallax-tolerant Image Stitchi

Kaimo Lin, NUS:

Nianjuan Jiang, Advanced Digital Sciences Center (ADSC):

Loong-Fah Cheong, National University of Singapore:

Minh Do, University of Illinois at Urbana-Champaign:

Jiangbo Lu, ADSC Singapore:

【Image editing】P-2B-26.   Deep Joint Image Filter

PDF: http://www.eccv2016.org/files/posters/P-2B-26.pdf

Yijun Li, UC Merced:

Jia-Bin Huang, University of Illinois, Urbana-Champaign:

Narendra Ahuja, University of Illinois at Urbana-Champaign: http://vision.ai.illinois.edu/publications.htm

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Image editing】P-2B-32.   Automatic Attribute Discovery with Neural Activations

PDF: http://www.eccv2016.org/files/posters/P-2B-32.pdf

Sirion Vittayakorn, University of North Carolina at Chapel Hill:

Takayuki Umeda, NTT:

Kazuhiko Murasaki, NTT:

Kyoko Sudo, NTT:

Takayuki Okatani, Tohoku University:

Kota Yamaguchi, Tohoku University: http://vision.is.tohoku.ac.jp/~kyamagu/

【Image editing】P-2B-33. “What happens if…” Learning to predict the effect of forces in imag

Roozbeh Mottaghi, Allen Institute for AI: http://www.cs.stanford.edu/~roozbeh/

Mohammad Rastegari, AI2:

Abhinav Gupta,: http://www.cs.cmu.edu/~abhinavg/

Ali Farhadi, University of Washington: http://homes.cs.washington.edu/~ali/index.html

【Image editing】P-3A-12.   Patch-based low-rank matrix completion for learning of shape and motion models from few training samples

PDF: http://www.eccv2016.org/files/posters/P-3A-12.pdf

Jan Ehrhardt,:

Matthias Wilms, University of Lübeck:

Heinz Handels:

【Image editing】P-3B-38.   MARLow: A Joint Multiplanar Autoregressive and Low-Rank Approach for Image Completion

PDF: http://www.eccv2016.org/files/posters/P-3B-38.pdf

Mading Li, Peking University:

Jiaying Liu, Peking University:

Zhiwei Xiong,:

Xiaoyan Sun,:

Zongming Guo, Peking University:

【Image editing】P-4A-28.   Mesh Flow: Minimum Latency Online Video Stabilization

PDF: http://www.eccv2016.org/files/posters/P-4A-28.pdf

Shuaicheng Liu, Uestc.edu.cn:

ping tan,:

Lu Yuan, Microsoft Research Asia: http://research.microsoft.com/en-us/um/people/luyuan/index.htm

Jian Sun, Microsoft Research China: http://research.microsoft.com/en-us/groups/vc/

Bing Zeng, uestc.edu.cn:

【Image editing】P-4B-12.   Cluster Sparsity Field for Hyperspectral Imagery Denoising

PDF: http://www.eccv2016.org/files/posters/P-4B-12.pdf

Lei Zhang, NPU: http://www4.comp.polyu.edu.hk/~cslzhang/

Wei Wei, Northwestern Polytechnical University:

yanning Zhang, Northwestern Polytechnical University:

Chunhua Shen, University of Adelaide:

Anton Van den Hengel, University of Adelaide:

Qinfeng Shi, The University of Adelaide:

【Computational photography】P-1A-26.   A Software Platform for Manipulating the Camera Imaging Pipeline

PDF: http://www.eccv2016.org/files/posters/P-1A-26.pdf

Hakki Karaimer, NUS:

Michael Brown, NUS: http://www.comp.nus.edu.sg/~brown/

【Computational photography】P-1A-30.   Localizing and Orienting Street Views Using Overhead Imagery

PDF: http://www.eccv2016.org/files/posters/P-1A-30.pdf

Nam Vo, Georgia Institute of Technology:

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

【Computational photography】P-1A-38.   Building Dual-Domain Representations for Compression Artifacts Reduction

PDF: http://www.eccv2016.org/files/posters/P-1A-38.pdf

Jun Guo, Sun Yat-Sen University:

Hongyang Chao, Sun Yat-sen University:

【Computational photography】P-1A-40.   Photo Aesthetics Ranking Network with Attributes and Content Adaptation

PDF: http://www.eccv2016.org/files/posters/P-1A-40.pdf

Shu Kong, UCI:

Xiaohui Shen, Adobe:

Zhe Lin, Adobe Systems, Inc.: http://www.adobe.com/technology/people/san-jose/zhe-lin.html

Radomir Mech, Adobe:

Charless Fowlkes: http://www.ics.uci.edu/~fowlkes/

【Computational photography】P-1B-14.   Single Image Dehazing via Multi-Scale Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-1B-14.pdf

Wenqi Ren, Tianjin University:

Si Liu, Chinese Academy of Sciences:

Hua Zhang, iie.ac.cn:

Jinshan Pan, UC Merced:

Xiaochun Cao, Chinese Academy of Sciences:

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Computational photography】P-1B-24.   Deep Warp: Photorealistic Image Resynthesis for Gaze Manipulation

PDF: http://www.eccv2016.org/files/posters/P-1B-24.pdf

Yaroslav Ganin, Skoltech:

Daniil Kononenko, Skoltech:

Diana Sungatullina, Skoltech:

Victor Lempitsky, Skolkovo Institute of Science and Technology:

【Computational photography】P-1B-29.   Accelerating the Super-Resolution Convolutional Neural Network

PDF: http://www.eccv2016.org/files/posters/P-1B-29.pdf

CHAO DONG, The Chinese University of HK:

Chen-Change Loy, the Chinese University of Hong Kong:

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

【Computational photography】P-1B-35.   An Occlusion-Resistant Ellipse Detection Method by Joining Coelliptic Arcs

PDF: http://www.eccv2016.org/files/posters/P-1B-35.pdf

Halil Cakir, Dumlupinar University:

Cihan Topal,:

Cuneyt Akinlar:

【Computational photography】P-1B-39.   Stereo Video Deblurring

PDF: http://www.eccv2016.org/files/posters/P-1B-39.pdf

Anita Sellent, Technische Universität Darmstadt, Technische Universität Dresden:

Carsten Rother,: http://www.inf.tu-dresden.de/index.php?node_id=3517&ln=de

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

【Computational photography】P-1B-40.   Robust Image and Video Dehazing with Visual Artifact Suppression via Gradient Residual Minimization

PDF: http://www.eccv2016.org/files/posters/P-1B-40.pdf

Chen Chen, UIUC:

Minh Do, University of Illinois at Urbana-Champaign:

Jue Wang, Adobe Research: http://www.juew.org/

【Computational photography】P-1B-42.   Title Generation for User Generated Videos

PDF: http://www.eccv2016.org/files/posters/P-1B-42.pdf

Kuo-Hao Zeng, National Tsing Hua University:

Tseng-Hung Chen, National Tsing Hua University:

Juan Carlos Niebles, Stanford University:

Min Sun, National Tsing Hua University:

【Computational photography】P-1B-47.   Perceptual Losses for Real-Time Style Transfer and Super-Resolution

PDF: http://www.eccv2016.org/files/posters/P-1B-47.pdf

Justin Johnson, Stanford University:

Alexandre Alahi, Stanford University:

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

【Computational photography】P-2A-17. Hierarchical Beta Process with Gaussian Process prior for Hyperspectral Image Super Resoluti

Naveed Akhtar, Uni. of Western Australia:

Faisal Shafait,:

Ajmal Mian, UWA:

【Computational photography】P-2A-20.   All-around Depth from Small Motion with A Spherical Panoramic Camera

PDF: http://www.eccv2016.org/files/posters/P-2A-20.pdf

Sunghoon Im, KAIST:

Hyowon Ha, KAIST:

Francois Rameau,:

Hae-Gon Jeon, KAIST:

Gyeongmin Choe, KAIST:

In So Kweon, KAIST: http://rcv.kaist.ac.kr/

【Computational photography】S-2B-05. An evaluation of computational imaging techniques for heterogeneous inverse scatteri

Ioannis Gkioulekas, Harvard University:

Todd Zickler,:

Anat Levin, Weizmann Institute of Science: http://www.wisdom.weizmann.ac.il/~levina/

【Computational photography】S-2B-08.   Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs

PDF: http://www.eccv2016.org/files/posters/S-2B-08.pdf

Lei Xiao, University of British Columbia:

Jue Wang, Adobe Research: http://www.juew.org/

Wolfgang Heidrich, KAUST:

Michael Hirsch:

【Computational photography】S-2B-09.   Multi-View Inverse Rendering under Arbitrary Illumination and Albedo

PDF: http://www.eccv2016.org/files/posters/S-2B-09.pdf

Kichang Kim, Tokyo Institute of Technology:

Akihiko Torii, Tokyo Institute of Technology:

Masatoshi Okutomi, Tokyo Institute of Technology:

【Computational photography】O-2B-01. The Fast Bilateral Solv

Jonathan Barron, Google:

Ben Poole, Stanford University:

【Computational photography】O-2B-03.   Colorful Image Colorization

PDF: http://www.eccv2016.org/files/posters/O-2B-03.pdf

Richard Zhang, UC Berkeley:

Phillip Isola, MIT:

Alexei Efros: http://www.cs.cmu.edu/~efros/

【Computational photography】S-2B-05. An evaluation of computational imaging techniques for heterogeneous inverse scatteri

Ioannis Gkioulekas, Harvard University:

Todd Zickler,:

Anat Levin, Weizmann Institute of Science: http://www.wisdom.weizmann.ac.il/~levina/

【Computational photography】S-2B-08.   Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs

PDF: http://www.eccv2016.org/files/posters/S-2B-08.pdf

Lei Xiao, University of British Columbia:

Jue Wang, Adobe Research: http://www.juew.org/

Wolfgang Heidrich, KAUST:

Michael Hirsch:

【Computational photography】S-2B-09.   Multi-View Inverse Rendering under Arbitrary Illumination and Albedo

PDF: http://www.eccv2016.org/files/posters/S-2B-09.pdf

Kichang Kim, Tokyo Institute of Technology:

Akihiko Torii, Tokyo Institute of Technology:

Masatoshi Okutomi, Tokyo Institute of Technology:

【Computational photography】P-2B-21.   From Multiview Image Curves to 3D Drawings

PDF: http://www.eccv2016.org/files/posters/P-2B-21.pdf

Anil Usumezbas, Brown University:

Ricardo Fabbri, State University of Rio de Janeiro:

Benjamin Kimia, Brown University:

【Computational photography】P-2B-34.   View synthesis by appearance flow

PDF: http://www.eccv2016.org/files/posters/P-2B-34.pdf

Tinghui Zhou, UC Berkeley:

Shubham Tulsiani, UC Berkeley:

Weilun Sun, UC Berkeley:

Jitendra Malik, UC Berkeley: http://www.cs.berkeley.edu/~malik/

Alexei Efros: http://www.cs.cmu.edu/~efros/

【Computational photography】P-2B-39.   Deep Specialized Network for Illuminant Estimation

PDF: http://www.eccv2016.org/files/posters/P-2B-39.pdf

Wu Shi, The Chinese University of HK:

Chen-Change Loy, the Chinese University of Hong Kong:

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

【Computational photography】O-3A-03.   Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network

PDF: http://www.eccv2016.org/files/posters/O-3A-03.pdf

Sifei Liu, UC Merced:

Jinshan Pan, UC Merced:

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Computational photography】O-3A-04.   Learning Representations for Automatic Colorization

PDF: http://www.eccv2016.org/files/posters/O-3A-04.pdf

Gustav Larsson, University of Chicago:

Michael Maire, Toyota Technological Institute at Chicago: http://ttic.uchicago.edu/~mmaire/

Greg Shakhnarovich, TTI Chicago, USA:

【Computational photography】O-3A-03.   Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network

PDF: http://www.eccv2016.org/files/posters/O-3A-03.pdf

Sifei Liu, UC Merced:

Jinshan Pan, UC Merced:

Ming-Hsuan Yang, UC Merced: http://faculty.ucmerced.edu/mhyang/

【Computational photography】O-3A-04.   Learning Representations for Automatic Colorization

PDF: http://www.eccv2016.org/files/posters/O-3A-04.pdf

Gustav Larsson, University of Chicago:

Michael Maire, Toyota Technological Institute at Chicago: http://ttic.uchicago.edu/~mmaire/

Greg Shakhnarovich, TTI Chicago, USA:

【Computational photography】P-3A-16.   Attribute2Image: Conditional Image Generation from Visual Attributes

PDF: http://www.eccv2016.org/files/posters/P-3A-16.pdf

Xinchen Yan, University of Michigan:

Jimei Yang, Abode Research: https://eng.ucmerced.edu/people/jyang44

Kihyuk Sohn, NEC Lab:

Honglak Lee: http://web.eecs.umich.edu/~honglak/

【Computational photography】P-3A-18.   Friction from Reflectance: Deep Reflectance Codes for Predicting Physical Surface Properties from One-Shot In-Field Reflectance

PDF: http://www.eccv2016.org/files/posters/P-3A-18.pdf

Hang Zhang, Rutgers University:

Kristin Dana, Rutgers University:

Ko Nishino, Drexel University:

【Computational photography】P-3A-22.   Image Quality Assessment Using Similar Scene as Reference

PDF: http://www.eccv2016.org/files/posters/P-3A-22.pdf

Yudong Liang, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University:

Jinjun Wang,:

Xingyu Wan, xjtu.edu.cn:

Yihong Gong,:

Nanning Zheng, Xi:

an Jiaotong University:

【Computational photography】P-3A-33.   Natural Image Stitching with the Global Similarity Prior

PDF: http://www.eccv2016.org/files/posters/P-3A-33.pdf

Yu-Sheng Chen, National Taiwan University:

Yung-Yu Chuang, National Taiwan University:

【Computational photography】P-3A-41.   Ultra Resolution by Discriminative Generative Networks

PDF: http://www.eccv2016.org/files/posters/P-3A-41.pdf

Xin Yu, Australian National University:

Fatih Porikli, Australian National University: http://www.porikli.com/

【Computational photography】D-3A-49. Deep Warp: Photorealistic Image Resynthesis for Gaze Manipulation

Yaroslav Ganin, Skolkovo Institute of Science and Technology:

Daniil Kononenko, Skolkovo Institute of Science and Technology:

Diana Sungatullina, Skolkovo Institute of Science and Technology:

Victor Lempitsky, Skolkovo Institute of Science and Technology:

【Computational photography】P-3B-34.   Deep Decoupling of Defocus and Motion Blur for Dynamic Segmentation

PDF: http://www.eccv2016.org/files/posters/P-3B-34.pdf

Abhijith Punnappurath, IIT Madras:

YOGESH BALAJI, IIT MADRAS:

Mahesh Mohan M R, IIT Madras:

A N Rajagopalan, Indian Institute of Technology, Madras:

【Computational photography】S-3C-07.   Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural Fields

PDF: http://www.eccv2016.org/files/posters/S-3C-07.pdf

Seungryong Kim, Yonsei University:

Kihong Park, Yonsei Univ.:

Kwanghoon Sohn, Yonsei university:

Stephen Lin, Microsoft Research Asia, China:

【Computational photography】P-3C-26.   Depth-aware Motion Magnification

PDF: http://www.eccv2016.org/files/posters/P-3C-26.pdf

Julian Kooij, Delft University of Technology:

Jan van Gemert, Delft University of Technology:

【Computational photography】P-3C-35.   Sparse Representation Based Complete Kernel Marginal Fisher Analysis Framework for Computational Art Painting Categorization

PDF: http://www.eccv2016.org/files/posters/P-3C-35.pdf

Ajit Puthenputhussery, New Jersey Institute of Technology:

Qingfeng Liu, New Jersey Institute of Techno:

Chengjun Liu, New Jersey Institute of Technology:

【Computational photography】O-4A-03.   Dual Structured Light 3D using a 1D Sensor

PDF: http://www.eccv2016.org/files/posters/O-4A-03.pdf

Jian Wang, Carnegie Mellon University:

Aswin Sankaranarayanan, Carnegie Mellon University:

Mohit Gupta,:

Srinivasa Narasimhan, CMU:

【Computational photography】P-4A-29. Large-scale training of shadow detectors with noisily-annotated shadow examples

Tomas F Yago Vicente, Stony Brook University:

Le Hou, Stony Brook University:

Chen-Ping Yu, Stony Brook University:

Minh Hoai, Stony Brook University:

Dimitris Samaras, SUNY Stonybrook:

【Computational photography】P-4B-11.   Deep Cascaded Bi-Network for Face Hallucination

PDF: http://www.eccv2016.org/files/posters/P-4B-11.pdf

Shizhan Zhu, Chinese University of HK:

Sifei Liu, UC Merced:

Chen-Change Loy, the Chinese University of Hong Kong:

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

【Texture analysis】O-1B-02.   Grounding of Textual Phrases in Images by Reconstruction

PDF: http://www.eccv2016.org/files/posters/O-1B-02.pdf

Anna Rohrbach:

Marcus Rohrbach, UC Berkeley:

Ronghang Hu, UC Berkeley:

Trevor Darrell, UC Berkeley: http://www.eecs.berkeley.edu/~trevor/

Bernt Schiele: http://www.d2.mpi-inf.mpg.de/schiele/

【Texture analysis】P-1B-27. Fine-grained material classification using micro-geometry and reflectan

Christos Kampouris, Imperial College London:

Stefanos Zafeiriou, Imperial College London:

Abhijeet Ghosh, Imperial College London:

Sotirios Malassiotis, Centre for Research and Technology Hellas:

【Texture analysis】P-2A-18.   A 4D Light-Field Dataset and CNN Architectures for Material Recognition

PDF: http://www.eccv2016.org/files/posters/P-2A-18.pdf

Ting-Chun Wang, UC Berkeley:

Jun-Yan Zhu, UC BERKELEY:

Hiroaki Ebi, University of California, San:

Manmohan Chandraker, NEC Labs America:

Alexei Efros,: http://www.cs.cmu.edu/~efros/

Ravi Ramamoorthi:

【Texture analysis】P-2A-37. Large Scale Asset Extraction for Urban Imag

Lama Affara, KAUST:

Liangliang Nan, KAUST:

Bernard Ghanem, KAUST:

Peter Wonka:

【Texture analysis】S-2B-06.   Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

PDF: http://www.eccv2016.org/files/posters/S-2B-06.pdf

Chuan Li, University of Mainz:

Michael Wand, University of Mainz:

【Texture analysis】S-2B-06.   Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

PDF: http://www.eccv2016.org/files/posters/S-2B-06.pdf

Chuan Li, University of Mainz:

Michael Wand, University of Mainz:

【Data clustering】O-2A-02.  -Sparse Subspace Clustering

PDF: http://www.eccv2016.org/files/posters/O-2A-02.pdf

Yingzhen Yang, UIUC:

Jiashi Feng, NUS:

Nebojsa Jojic, Microsoft Research:

Jianchao Yang, Snapchat: http://www.ifp.illinois.edu/~jyang29/

Thomas Huang, UIUC:

【Data clustering】O-2A-03.   Normalized Cut meets MRF

PDF: http://www.eccv2016.org/files/posters/O-2A-03.pdf

Meng Tang, UWO:

Dmitrii Marin, UWO:

Ismail Ben Ayed, École de technologie supérieure:

Yuri Boykov, University of Western Ontario: http://www.csd.uwo.ca/~yuri/

【Machine learning】P-1A-22.   Gaussian Process Density Counting from Weak Supervision

PDF: http://www.eccv2016.org/files/posters/P-1A-22.pdf

Matthias von Borstel, Heidelberg University:

Melih Kandemir, Heidelberg University:

Philip Schmidt, Heidelberg University:

Madhavi Kachur Rao, Robert Bosch:

Kumar Rajamani, Bosch India:

Fred Hamprecht, Heidelberg University:

【Machine learning】P-1A-32.   Shuffle and Learn: Unsupervised Learning using Temporal Order Verification

PDF: http://www.eccv2016.org/files/posters/P-1A-32.pdf

Ishan Misra, CMU:

Larry Zitnick,:

Martial Hebert, Carnegie Mellon University: http://www.cs.cmu.edu/~hebert/

【Machine learning】P-1A-37.   Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies

PDF: http://www.eccv2016.org/files/posters/P-1A-37.pdf

Emanuel Laude, Technical University of Munich:

Thomas Möllenhoff,:

Michael Moeller, TUM:

Jan Lellmann,:

Daniel Cremers: http://vision.in.tum.de/

【Machine learning】P-1B-11.   Playing for Data: Ground Truth from Computer Games

PDF: http://www.eccv2016.org/files/posters/P-1B-11.pdf

Stephan Richter, TU Darmstadt:

Vibhav Vineet, Intel Labs:

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

Vladlen Koltun, Intel Labs: http://vladlen.info/publications/

【Machine learning】P-1B-13. Revisiting additive quantizati

Julieta Martinez, University of British Columbia:

Joris Clement, University of British Columbia:

Holger Hoos, University of British Columbia:

Jim Little, University of British Columbia:

【Machine learning】P-1B-36.   Branching Path Following for Graph Matching

PDF: http://www.eccv2016.org/files/posters/P-1B-36.pdf

Tao Wang, Beijing Jiaotong University:

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

Congyan Lang, Beijing Jiaotong University:

Jun Wu, Beijing Jiaotong University:

【Machine learning】P-1B-37.   Higher Order Conditional Random Fields in Deep Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-1B-37.pdf

Anurag Arnab, University of Oxford:

Sadeep Jayasumana, University of Oxford:

Shuai Zheng, University of Oxford:

Philip Torr, Oxford University: http://www.robots.ox.ac.uk/~tvg/

【Machine learning】P-1B-41.   Smooth Neighborhood Structure Mining on Multiple Affinity Graphs with Applications to Context-sensitive Similarity

PDF: http://www.eccv2016.org/files/posters/P-1B-41.pdf

Song Bai, HUST:

Shaoyan Sun, University of Science and Technology of China:

Xiang Bai, Huazhong University of Science and Technology:

Zhaoxiang Zhang, Institute of Automation, Chinese Academy of Sciences: http://irip.buaa.edu.cn/~zxzhang/index.html

Qi Tian: http://www.cs.utsa.edu/~qitian/

【Machine learning】P-1B-44.   Double-Opponent Vectorial Total Variation

PDF: http://www.eccv2016.org/files/posters/P-1B-44.pdf

Freddie Astrom, Heidelberg University:

Christoph Schnoerr, Heidelberg University:

【Machine learning】O-2A-01.   An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem

PDF: http://www.eccv2016.org/files/posters/O-2A-01.pdf

Thorsten Beier, University of Heidelberg:

Bjoern Andres, Max-Planck Institute for Informatics:

Ullrich Koethe, University of Heidelberg:

Fred Hamprecht, Heidelberg University:

【Machine learning】S-2A-05. Polysemous Cod

Matthijs Douze:

Herve Jegou:

Florent Perronnin, Facebook:

【Machine learning】S-2A-07.   Efficient Continuous Relaxations for Dense CRF

PDF: http://www.eccv2016.org/files/posters/S-2A-07.pdf

Rudy Bunel, University of Oxford:

Alban Desmaison, University of Oxford:

  1. Pawan Kumar, University of Oxford:

Philip Torr, Oxford University: http://www.robots.ox.ac.uk/~tvg/

Pushmeet Kohli, Microsoft Research Cambridge: http://research.microsoft.com/en-us/um/people/pkohli/

【Machine learning】S-2A-08.   Complexity of Discrete Energy Minimization Problems

PDF: http://www.eccv2016.org/files/posters/S-2A-08.pdf

Mengtian Li, Carnegie Mellon University:

Alexander Shekhovtsov, Graz University of Technology: http://cmp.felk.cvut.cz/~shekhovt/

Daniel Huber:

【Machine learning】S-2A-09.   A Convex Solution to Spatially-Regularized Correspondence Problems

PDF: http://www.eccv2016.org/files/posters/S-2A-09.pdf

Thomas Windheuser, TU Muenchen:

Daniel Cremers: http://vision.in.tum.de/

【Machine learning】P-2A-10.   Jensen Bregman Log Det Divergence Optimal Filtering in the Manifold of Positive Definite Matrices

PDF: http://www.eccv2016.org/files/posters/P-2A-10.pdf

Yin Wang, northeastern University:

Octavia Camps, Northeastern University:

Mario Sznaier, Northeastern University:

Biel Roig Solvas, Northeastern University:

【Machine learning】P-2A-11.   Reflection Symmetry Detection via Appearance of Structure Descriptor

PDF: http://www.eccv2016.org/files/posters/P-2A-11.pdf

Ibragim Atadjanov, KHU:

Seungkyu Lee, Kyung Hee University:

【Machine learning】P-2A-22.   Multi-attributed Graph Matching with Multi-layer Random Walks

PDF: http://www.eccv2016.org/files/posters/P-2A-22.pdf

Han-Mu Park, GIST:

Kuk-Jin Yoon, Gwangju Institute of Science and Technology: https://cvl.gist.ac.kr/introduction.html

【Machine learning】P-2A-30.   A simple hierarchical pooling data structure for loop closure

PDF: http://www.eccv2016.org/files/posters/P-2A-30.pdf

Xiaohan Fei, UCLA:

Konstantine Tsotsos,:

Stefano Soatto, University of California, Los Angeles: http://vision.ucla.edu/projects.html

【Machine learning】P-2A-31. A Versatile Approach for Solving Pn P, Pn Pf, and Pn Pfr Proble

Gaku Nakano, NEC Corporation:

【Machine learning】P-2A-45.   Abundant Inverse Regression using Sufficient Reduction and its applications

PDF: http://www.eccv2016.org/files/posters/P-2A-45.pdf

Hyunwoo Kim, UW-Madison:

Brandon Smith, UW-Madison:

Nagesh Adluru, UW-Madison:

Charles Dyer, University of Wisconsin – Madison:

Sterling Johnson, UW-Madison:

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

【Machine learning】P-2A-46. Learning Diverse Models: The Coulomb Structured Support Vector Machi

Martin Schiegg, University of Heidelberg:

Robert Bosch Gmb H:

Ferran Diego, University of Heidelberg, HCI:

Fred Hamprecht, Heidelberg University:

【Machine learning】P-2B-27.   Efficient Multi-Frequency Phase Unwrapping using Kernel Density Estimation

PDF: http://www.eccv2016.org/files/posters/P-2B-27.pdf

Felix Jaremo-Lawin, Linkoping University:

Per-Erik Forssen, Linkoping University:

Hannes Ovren, Linköping university:

【Machine learning】P-3A-36.   Automatically selecting inference algorithms for discrete energy minimisation

PDF: http://www.eccv2016.org/files/posters/P-3A-36.pdf

Paul Henderson, University of Edinburgh:

Vittorio Ferrari: http://groups.inf.ed.ac.uk/calvin/index.html

【Machine learning】P-3A-46.   Transfer Neural Trees for Heterogeneous Domain Adaptation

PDF: http://www.eccv2016.org/files/posters/P-3A-46.pdf

Wei Yu Chen, NTU:

Academia Sinica:

Tzu-Ming Hsu,:

Yao-Hung Tsai, Academia Sinica:

Yu-Chiang Frank Wang, Academia Sinica: http://www.citi.sinica.edu.tw/pages/ycwang/index_en.html

Ming-Syan Chen, National Taiwan University:

【Machine learning】P-3B-10.   Extending Long Short-Term Memory for Multi-View Structured Learning

PDF: http://www.eccv2016.org/files/posters/P-3B-10.pdf

Shyam Sundar Rajagopalan, University of Canberra:

Louis-Philippe Morency, Carnegie Mellon University:

Tadas Baltrušaitis, Carnegie Mellon University:

Roland Goecke, University of Canberra:

【Machine learning】P-3B-16.   Iterative Reference Driven Metric Learning for Signer Independent Isolated Sign Language Recognition

PDF: http://www.eccv2016.org/files/posters/P-3B-16.pdf

Fang Yin, ICT,CAS:

Xiujuan Chai, ICT, CAS:

Xilin Chen, Institute of Computing Technology, Chinese Academy of Sciences:

【Machine learning】D-3B-49. Extracting Driving Behavior: Global Metric Localization from Dashcam Videos in the Wild

Shao-Pin Chang, National Tsing Hua University:

Jui-Ting Chien, National Tsing Hua University:

Fu-En Wang, National Tsing Hua University:

Shang-Da Yang, National Tsing Hua University:

Hwann-Tzong Chen, National Tsing Hua University: http://www.cs.nthu.edu.tw/~htchen/

Min Sun, National Tsing Hua University:

【Machine learning】P-3C-11.   Inter-Battery Topic Representation Learning

PDF: http://www.eccv2016.org/files/posters/P-3C-11.pdf

Cheng Zhang, KTH Royal Institute of Technology:

Hedvig Kjellstrom,:

Carl Henrik Ek:

【Machine learning】P-3C-29.   Pixel-Level Domain Transfer

PDF: http://www.eccv2016.org/files/posters/P-3C-29.pdf

Donggeun Yoo, KAIST:

Namil Kim, KAIST:

Sunggyun Park, KAIST:

Anthony Paek, Lunit Inc.:

In So Kweon, KAIST: http://rcv.kaist.ac.kr/

【Machine learning】P-3C-33.   Efficient and Robust Semi-supervised Learning over a Sparse-Regularized Graph

PDF: http://www.eccv2016.org/files/posters/P-3C-33.pdf

Hang Su, Tsinghua University:

Jun Zhu, Tsinghua University:

Zhaozheng Yin, Missouri University of Science and Technology:

Yinpeng Dong, Tsinghua University:

Bo Zhang, Tsinghua University:

【Machine learning】S-4A-07.   A Distance for HMMs based on Aggregated Wasserstein Metric and State Registration

PDF: http://www.eccv2016.org/files/posters/S-4A-07.pdf

Yukun Chen, Penn State University:

Jianbo Ye, College of Information Sciences and Technology, Penn State University:

Jia Li, Department of Statistics, Penn State University:

【Machine learning】P-4A-11.   Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data

PDF: http://www.eccv2016.org/files/posters/P-4A-11.pdf

Guobao Xiao, Xiamen University:

Hanzi Wang,:

Yan Yan,:

David Suter:

【Machine learning】P-4A-14.   Deep Robust Encoder through Locality Preserving Low-Rank Dictionary

PDF: http://www.eccv2016.org/files/posters/P-4A-14.pdf

Zhengming Ding, Northeastern University:

Ming Shao, Northeastern University:

Yun Fu, Northeastern University:

【Machine learning】P-4A-17.   Learning to Learn: Model Regression Networks for Easy Small Sample Learning

PDF: http://www.eccv2016.org/files/posters/P-4A-17.pdf

Yu-Xiong Wang, Carnegie Mellon University:

Martial Hebert, Carnegie Mellon University: http://www.cs.cmu.edu/~hebert/

【Machine learning】P-4A-23.   Biconvex Relaxation for Semidefinite Programming in Computer Vision

PDF: http://www.eccv2016.org/files/posters/P-4A-23.pdf

Sohil Shah, University of Maryland:

Abhay Yadav, University Of Maryland:

Carlos Castillo, University of Maryland, CP:

David Jacobs, University of Maryland:

Christoph Studer, Cornell University:

Tom Goldstein, University of Maryland, College Park:

【Machine learning】P-4A-27.   Stochastic Dykstra Algorithms for Metric Learning with Positive Definite Covariance Descriptors

PDF: http://www.eccv2016.org/files/posters/P-4A-27.pdf

Tsuyoshi Kato, Gunma University:

Tomoki Matsuzawa, Gunma University:

Jun Sese,:

Raissa Relator:

【Machine learning】P-4A-34.   Sparse Recovery of Hyperspectral Signal from Natural RGB Images

PDF: http://www.eccv2016.org/files/posters/P-4A-34.pdf

Boaz Arad, BGU:

Ohad Ben-Shahar, Ben-Gurion University:

【Machine learning】P-4B-10.   Generative Visual Manipulation on the Natural Image Manifold

PDF: http://www.eccv2016.org/files/posters/P-4B-10.pdf

Jun-Yan Zhu, UC BERKELEY:

Philipp Krahenbuhl,:

Eli Shechtman, Adobe: http://www.adobe.com/technology/people/seattle/eli-shechtman.html

Alexei Efros,: http://www.cs.cmu.edu/~efros/

【Machine learning】P-4B-15.   MADMM: a generic algorithm for non-smooth optimization on manifolds

PDF: http://www.eccv2016.org/files/posters/P-4B-15.pdf

Artiom Kovnatsky, USI-Università della Svizzera:

Klaus Glashoff, USI-Università della Svizzera italiana:

Michael Bronstein:

【Machine learning】P-4B-17.   Semi-supervised learning based on joint diffusion of graph functions and Laplacians

PDF: http://www.eccv2016.org/files/posters/P-4B-17.pdf

Kwang In Kim, University of Bath:

【Machine learning】P-4B-25.   Partial Linearization based Optimization for Multi-class SVM

PDF: http://www.eccv2016.org/files/posters/P-4B-25.pdf

Pritish Mohapatra, IIIT, Hyderabad:

Puneet Dokania, Ecole Centrale Paris:

C.V. Jawahar, IIIT Hyderabad:

  1. Pawan Kumar, University of Oxford:

【Machine learning】P-4B-27.   Scalable Metric Learning via Weighted Approximate Rank Component Analysis

PDF: http://www.eccv2016.org/files/posters/P-4B-27.pdf

Cijo Jose, Idiap Research Institute:

Francois Fleuret:

【Machine learning】P-4B-44.   Weakly Supervised Learning of Heterogeneous Concepts in Videos

PDF: http://www.eccv2016.org/files/posters/P-4B-44.pdf

Sohil Shah, University of Maryland:

Kuldeep Kulkarni, Arizona State University:

Arijit Biswas, Amazon Development Center India:

Ankit Gandhi, Xerox Research Centre India:

Om Deshmukh, Xerox Research Centre India:

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

【Deep learning】P-1A-20.   Contextual Priming & Feedback for Faster R-CNN

PDF: http://www.eccv2016.org/files/posters/P-1A-20.pdf

Abhinav Shrivastava, Carnegie Mellon University:

Abhinav Gupta: http://www.cs.cmu.edu/~abhinavg/

【Deep learning】P-1A-39.   Geometric Neural Phrase Pooling: Modeling the Spatial Co-occurrence of Neurons

PDF: http://www.eccv2016.org/files/posters/P-1A-39.pdf

Lingxi Xie, UCLA:

Qi Tian,: http://www.cs.utsa.edu/~qitian/

John Flynn, UCLA:

Jingdong Wang, Microsoft Research:

Alan Yuille, UCLA: http://www.stat.ucla.edu/~yuille/

【Deep learning】P-1B-10.   Taxonomy-Regularized Semantic Deep Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-1B-10.pdf

Wonjoon Goo, Seoul National University:

Juyong Kim, Seoul National University:

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

Sung Ju Hwang, UNIST:

【Deep learning】P-1B-45. Learning to Count with CNN Boosti

Elad Walach , Tel Aviv University:

Lior Wolf:

【Deep learning】P-2A-35.   Large-scale R-CNN with Classifier Adaptive Quantization

PDF: http://www.eccv2016.org/files/posters/P-2A-35.pdf

Ryota Hinami, The University of Tokyo:

Shin’ichi Satoh, National Institute of Informatics, Japan:

【Deep learning】S-3A-05.   Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation

PDF: http://www.eccv2016.org/files/posters/S-3A-05.pdf

Muhammad Ghifary, VUW, Weta Digital:

Bastiaan Kleijn, Victoria University of Wellington:

Mengjie Zhang, Victoria University of Wellington:

David Balduzzi, Victoria University of Wellington:

Wen Li, ETH Zurich:

【Deep learning】S-3A-06. Learning without Forgetti

Zhizhong Li, UIUC:

Derek Hoiem, UIUC: http://www.cs.illinois.edu/~dhoiem/

【Deep learning】S-3A-07.   Identity Mappings in Deep Residual Networks

PDF: http://www.eccv2016.org/files/posters/S-3A-07.pdf

Kaiming He, Microsoft Research Asia: http://research.microsoft.com/en-us/um/people/kahe/

Xiangyu Zhang, Xi’an Jiaotong University:

Shaoqing Ren, University of Science & Technology of China:

Jian Sun, Microsoft Research China: http://research.microsoft.com/en-us/groups/vc/

【Deep learning】S-3A-08.   Deep Networks with Stochastic Depth

PDF: http://www.eccv2016.org/files/posters/S-3A-08.pdf

Gao Huang, Cornell University:

Yu Sun, Cornell University:

Zhuang Liu, Tsinghua University:

Daniel Sedra, Cornell University:

Kilian Weinberger, Cornell University:

【Deep learning】S-3A-09.   Less is More: Towards Compact CNNs

PDF: http://www.eccv2016.org/files/posters/S-3A-09.pdf

Hao Zhou, University of Maryland:

Jose M. Alvarez, Data61 / CSIRO:

Fatih Porikli, Australian National University: http://www.porikli.com/

【Deep learning】P-3B-13.   Reliable Fusion of To F and Stereo Depth Driven by Confidence Measures

PDF: http://www.eccv2016.org/files/posters/P-3B-13.pdf

Giulio Marin, University of Padova:

Pietro Zanuttigh, University of Padova:

Stefano Mattoccia, University of Bologna:

【Deep learning】P-3B-18.   Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3B-18.pdf

Li Shen, UCAS:

Zhouchen Lin, Peking University: http://www.cis.pku.edu.cn/faculty/vision/zlin/zlin.htm

Qingming Huang, University of Chinese Academy of Sciences:

【Deep learning】P-3B-33.   Collaborative Layer-wise Discriminative Learning in Deep Neural Networks

PDF: http://www.eccv2016.org/files/posters/P-3B-33.pdf

XIAOJIE JIN, National Univ. of Singapore:

YUNPENG CHEN, NUS:

Jian Dong, Qihoo/360:

Jiashi Feng, NUS:

Shuicheng Yan,: http://www.lv-nus.org/index.html

【Deep learning】P-3C-30.   Accelerating Convolutional Neural Networks with Dominant Convolutional Kernel and Knowledge Pre-regression

PDF: http://www.eccv2016.org/files/posters/P-3C-30.pdf

Zhenyang Wang, Tsinghua University:

Zhidong Deng, Tsinghua University:

Shiyao Wang, Tsinghua University:

【Deep learning】P-4A-12. Instance-sensitive Fully Convolutional Networks

Jifeng Dai, Microsoft Research Asia:

Kaiming He, Microsoft Research Asia: http://research.microsoft.com/en-us/um/people/kahe/

Yi Li, Tsinghua University: http://users.cecs.anu.edu.au/~yili/

Shaoqing Ren, University of Science & Technology of China:

Jian Sun, Microsoft Research China: http://research.microsoft.com/en-us/groups/vc/

 

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