Thomas Brox Thomas Brox
【Bio】Professor,leader of a group
【Focus on】video analysis, deep learning, and 3D representations

  • 2017 CVPR FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
  • 2016 ECCV Multi-view 3D Models from Single Images with a Convolutional Network
  • 2016 NIPS Generating Images with Perceptual Similarity Metrics based on Deep Networks
  • 2016 IROS Efficient Deep Methods for Monocular Road Segmentation
  • 2016 CVPR A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
  • 2015 ICCV FlowNet: Learning Optical Flow with Convolutional Networks
  • 2016 CVPR Inverting Convolutional Networks with Convolutional Networks
  • 2015 CVPR Learning to Generate Chairs with Convolutional Neural Networks
  • 2014 ECCV Dense semi-rigid scene flow estimation from RGBD images,
  • 2014 NIPS Discriminative Unsupervised Feature Learning with Convolutional Neural Networks
  • Image Descriptors based on Curvature Histograms,
  • Non-smooth Non-convexOptimization
  • Dense Label Interpolation
  • Motion Segmentation
  • Dense Point Tracking
  • Large Displacement Optical Flow
  • Classical Variational OpticalFlow
  • Nonlocal means with clustertrees

Carsten Rother Carsten Rother
【Bio】Professor,leader of a group
【Focus on】Machine Learning, Optimization, Biology, Computer Graphics, and Human Computer Interaction

  • 2015 CGF DenseCut: Densely Connected CRFs for Realtime GrabCut
  • Our code for intrinsic imagedecompostion is now online (based on the NIPS ’11 paper)
  • Software for fast and accuratestereo matching using a guided filter is available here, based on our CVPR ’11work
  • Interactive image segmentation:various methods and robot-user code (from CVPR ’10 paper) – see here
  • The software for optimizingMPFs [A Global Perspective on MAP Inference for Low-Level Vision, ICCV ’09] isavailabe … click here.
  • QPBO + P/I (from CVPR ’07paper) Please go to Vladimir Kolmogorov’s webpage to get the latest version.
  • Various Matting Methods (CVPR’09 paper) Please visit project page maintained by Christoph Rhemann
  • Optimizing Sparse Highero OrderClique MRFs (CVPR ’09 paper) we plan to make this code available soon
  • I have been involved in OpenGMSoftware

Daniel Cremers Daniel Cremers
【Bio】Professor,leader of a group
【Focus on】statistical inference, differential geometry, continuous (partial differential equations) and discrete (graph-theoretic) optimization techniques.

  • 2017 JMIV LED-based Photometric Stereo: Modeling, Calibration and Numerical Solution
  • 2017 EMMCVPR A Variational Approach to Shape-from-shading Under Natural Illumination
  • 2017 ICCVW Depth Super-Resolution Meets Uncalibrated Photometric Stereo
  • 2017 3DV Efficient Deformable Shape Correspondence via Kernel Matching
  • 2017 ICCV Associative Domain Adaptation
  • 2017 CVPR A Non-Convex Variational Approach to Photometric Stereo under Inaccurate Lighting
  • 2017 SSVM Semi-Calibrated Near-Light Photometric Stereo
  • 2017 CVPR Learning by Association – A versatile semi-supervised training method for neural networks
  • 2017 QCAV Microgeometry capture and RGB albedo estimation by photometric stereo without demosaicing
  • 2017 CVPR Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space
  • 2016 ACCV FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-based CNN Architecture
  • 2016 ECCV Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding
  • 2016 ECCV Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies
  • 2016 CVPR Sublabel-Accurate Relaxation of Nonconvex Energies
  • 2015 PRL A Simple and Effective Relevance-based Point Sampling for 3D Shapes
  • 2015 ICCV FlowNet: Learning Optical Flow with Convolutional Networks
  • 2015 CAPTCHA Recognition with Active Deep Learning
  • 2015 SSVM Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation
  • 2015 SSVM Interactive Multi-label Segmentation of RGB-D Images
  • 2014 ECCV Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional
  • 2013 ICCV Proportion Priors for Image Sequence Segmentation
  • 2014 CRA Volumetric 3D Mapping in Real-Time on a CPU
  • 2013 IJCV The cudaMultilabelOptimization library

Bastian Leibe Bastian Leibe
【Focus on】visual object recognition, tracking, self-localization, 3D reconstruction

  • 2017 ICCV Exploring Spatial Context for 3D Semantic Segmentation of Point Clouds
  • 2017 BMVC Online Adaptation of Convolutional Neural Networks for Video Object Segmentation
  • 2017 CVPR Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
  • 2017 CVPR Semi-Supervised Deep Learning for Monocular Depth Map Prediction
  • 2017 ICRA Combined Image- and World-Space Tracking in Traffic Scenes
  • 2017 ICRA DROW: Real-Time Deep Learning based Wheelchair Detection in 2D Range Data
  • 2017 WACV 3D Semantic Segmentation of Modular Furniture using rjMCMC
  • 2017 Arxiv Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters
  • 2017 Arxiv In Defense of the Triplet Loss for Person Re-Identification
  • 2016 GCPR Joint Object Pose Estimation and Shape Reconstruction in Urban Street Scenes Using 3D Shape Priors
  • 2016 Arxiv Superpixels: An Evaluation of the State-of-the-Art
  • 2015 GCPR Biternion Nets: Continuous Head Pose Regression from Discrete Training Labels
  • 2015 WACV Detecting Image Matches caused by Watermarks, Timestamps, and Frames in Internet Photos
  • 2014 BMVC Real-TimeRGB-D based People Detection and Tracking
  • GroundHOG -GPU-based Object Detection with Geometric Constraints
  • Implicit ShapeModel (ISM) detector code


Ing Jörn Ostermann Ing Jorn Ostermann
【Bio】Professor,leader of a group, PhD from Hannover
【Focus on】object segmentation, pose tracking, Bio-Medical Image Analysis,Audio Processing

Dariu M. Gavrila Dariu M. Gavrila
【Bio】Professor,leader of a group
【Focus on】smart car

Nassir Navab Nassir Navab
【Bio】Professor,leader of a group
【Focus on】Computer Aided Surgery,Industrial Augmented Reality