Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation
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Michael J. Black | Varun Jampani | Deqing Sun | Anurag Ranjan | Kihwan Kim | Lukas Balles | Jonas Wulff | Lukas Balles | Deqing Sun | Kihwan Kim | V. Jampani | Jonas Wulff | Anurag Ranjan
[1] Thomas Brox,et al. FlowNet: Learning Optical Flow with Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[2] Roberto Cipolla,et al. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[3] Jürgen Schmidhuber,et al. Neural Expectation Maximization , 2017, NIPS.
[4] Andrew Blake,et al. "GrabCut": interactive foreground extraction using iterated graph cuts , 2004, ACM Trans. Graph..
[5] Michael J. Black,et al. Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[7] Michael J. Black,et al. Optical Flow Estimation Using a Spatial Pyramid Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Thomas Brox,et al. A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Stefan Roth,et al. UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss , 2017, AAAI.
[11] Michael J. Black,et al. Mixture models for optical flow computation , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[12] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[13] Zhichao Yin,et al. GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[14] Luc Van Gool,et al. The 2017 DAVIS Challenge on Video Object Segmentation , 2017, ArXiv.
[15] Rob Fergus,et al. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network , 2014, NIPS.
[16] Michael J. Black,et al. Learning Human Optical Flow , 2018, BMVC.
[17] Thomas Brox,et al. DeMoN: Depth and Motion Network for Learning Monocular Stereo , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Michael J. Black,et al. Layered image motion with explicit occlusions, temporal consistency, and depth ordering , 2010, NIPS.
[19] Noah Snavely,et al. Unsupervised Learning of Depth and Ego-Motion from Video , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Michael J. Black,et al. Supplementary Material for Unsupervised Learning of Multi-Frame Optical Flow with Occlusions , 2018 .
[21] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[23] Ashutosh Saxena,et al. Learning Depth from Single Monocular Images , 2005, NIPS.
[24] Thomas Brox,et al. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Simon Haykin,et al. GradientBased Learning Applied to Document Recognition , 2001 .
[26] Konstantinos G. Derpanis,et al. Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness , 2016, ECCV Workshops.
[27] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] Ian D. Reid,et al. Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[30] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[31] Michael J. Black,et al. Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation , 2018, GCPR.
[32] Cordelia Schmid,et al. SfM-Net: Learning of Structure and Motion from Video , 2017, ArXiv.
[33] Andrew Y. Ng,et al. Reading Digits in Natural Images with Unsupervised Feature Learning , 2011 .
[34] Richard Szeliski,et al. A Database and Evaluation Methodology for Optical Flow , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[35] Michael J. Black,et al. A Naturalistic Open Source Movie for Optical Flow Evaluation , 2012, ECCV.
[36] Jan Kautz,et al. PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[37] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[38] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[39] Andreas Geiger,et al. Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[40] Jia-Bin Huang,et al. DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency , 2018, ECCV.
[41] Anelia Angelova,et al. Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[42] Gabriel J. Brostow,et al. Digging Into Self-Supervised Monocular Depth Estimation , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[43] Michael J. Black,et al. Optical Flow in Mostly Rigid Scenes , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).