Depth estimation/stereo matching/optical flow @CVPR 2017

1. Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation (PDF)
    Dan Xu, Elisa Ricci, Wanli Ouyang, Xiaogang Wang, Nicu Sebe
2. Semi-Supervised Deep Learning for Monocular Depth Map Prediction (PDF，PROJECT)
    Yevhen Kuznietsov, Jörg Stückler, Bastian Leibe
3. Accurate Depth and Normal Maps From Occlusion-Aware Focal Stack Symmetry (PDF)
    Michael Strecke, Anna Alperovich, Bastian Goldluecke
4. DeMoN: Depth and Motion Network for Learning Monocular Stereo (PDF，PROJECT)
    Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, Thomas Brox
5. Unsupervised Monocular Depth Estimation With Left-Right Consistency (PDF,PROJECT)
    Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow
6. Unsupervised Learning of Depth and Ego-Motion From Video (PDF)
    Tinghui Zhou, Matthew Brown, Noah Snavely, David G. Lowe
7. CATS: A Color and Thermal Stereo Benchmark (PDF,PROJECT)
    Wayne Treible, Philip Saponaro, Scott Sorensen, Abhishek Kolagunda, Michael O'Neal, Brian Phelan, Kelly Sherbondy, Chandra Kambhamettu
8. A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting (PDF)
    Yvain Quéau, Tao Wu, François Lauze, Jean-Denis Durou, Daniel Cremers
9. End-To-End Training of Hybrid CNN-CRF Models for Stereo (PDF,CODE)
    Patrick Knöbelreiter, Christian Reinbacher, Alexander Shekhovtsov, Thomas Pock
10. A Multi-View Stereo Benchmark With High-Resolution Images and Multi-Camera Videos (PDF,PROJECT)
    Thomas Schöps, Johannes L. Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, Andreas Geiger
11. Semi-Calibrated Near Field Photometric Stereo (PDF)
    Fotios Logothetis, Roberto Mecca, Roberto Cipolla
12. Semantic Multi-View Stereo: Jointly Estimating Objects and Voxels (PDF, PROJECT)
    Ali Osman Ulusoy, Michael J. Black, Andreas Geiger
13. Learning to Predict Stereo Reliability Enforcing Local Consistency of Confidence Maps (PDF)
    Matteo Poggi, Stefano Mattoccia
14. UltraStereo: Efficient Learning-Based Matching for Active Stereo Systems (PDF)
    Sean Ryan Fanello, Julien Valentin, Christoph Rhemann, Adarsh Kowdle, Vladimir Tankovich, Philip Davidson, Shahram Izadi
15. Fast Multi-Frame Stereo Scene Flow With Motion Segmentation (PDF, PROJECT)
    Tatsunori Taniai, Sudipta N. Sinha, Yoichi Sato
16. Improved Stereo Matching With Constant Highway Networks and Reflective Confidence Learning (PDF)
    Amit Shaked, Lior Wolf
17. Simultaneous Stereo Video Deblurring and Scene Flow Estimation (PDF)
    Liyuan Pan, Yuchao Dai, Miaomiao Liu, Fatih Porikli
18. Detect, Replace, Refine: Deep Structured Prediction for Pixel Wise Labeling (PDF)
    Spyros Gidaris, Nikos Komodakis
19. Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data (PDF)
    Joel Janai, Fatma Güney, Jonas Wulff, Michael J. Black, Andreas Geiger
20. FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks (PDF, PROJECT)
    Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, Thomas Brox
21. CNN-Based Patch Matching for Optical Flow With Thresholded Hinge Embedding Loss (PDF)
    Christian Bailer, Kiran Varanasi, Didier Stricker
22. Optical Flow Estimation Using a Spatial Pyramid Network (PDF)
    Anurag Ranjan, Michael J. Black
23. S2F: Slow-To-Fast Interpolator Flow (PDF)
    Yanchao Yang, Stefano Soatto
24. Robust Interpolation of Correspondences for Large Displacement Optical Flow (PDF)
    Yinlin Hu, Yunsong Li, Rui Song
25. Accurate Optical Flow via Direct Cost Volume Processing (PDF)
    Jia Xu, René Ranftl, Vladlen Koltun
26. InterpoNet, a Brain Inspired Neural Network for Optical Flow Dense Interpolation (PDF)
    Shay Zweig, Lior Wolf
27. Optical Flow in Mostly Rigid Scenes (PDF)
    Jonas Wulff, Laura Sevilla-Lara, Michael J. Black
28. Optical Flow Requires Multiple Strategies (but Only One Network) (PDF)

    Tal Schuster, Lior Wolf, David Gadot