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A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation.

, , , , , , и . CoRR, (2015)

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Alexey Shaytan

Alexey Dashevsky

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Striving for simplicity: The all convolutional net, , , и . arXiv preprint arXiv:1412.6806, (2014)Unsupervised Learning of Shape and Pose with Differentiable Point Clouds., и . NeurIPS, стр. 2807-2817. (2018)FlowNet: Learning Optical Flow with Convolutional Networks, , , , , , , , и . (2015)cite arxiv:1504.06852Comment: Added supplementary material.On Offline Evaluation of Vision-Based Driving Models., , , и . ECCV (15), том 11219 из Lecture Notes in Computer Science, стр. 246-262. Springer, (2018)Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing., , , , , , и . ICRA, стр. 690-696. IEEE, (2019)Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space., , , , и . CVPR, стр. 3510-3520. IEEE Computer Society, (2017)Deep Drone Racing: From Simulation to Reality with Domain Randomization., , , , , и . CoRR, (2019)Learning Depth via Interaction., , и . CoRR, (2020)Striving for Simplicity: The All Convolutional Net, , , и . 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings, (2015)Learning to Act by Predicting the Future., и . ICLR, OpenReview.net, (2017)