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What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?

Mar 22, 2018
Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox

* added references (UCL dataset); added IJCV copyright information 

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DeMoN: Depth and Motion Network for Learning Monocular Stereo

Apr 11, 2017
Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, Thomas Brox

* Camera ready version for CVPR 2017. Supplementary material included. Project page: 

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FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Dec 06, 2016
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, Thomas Brox

* Including supplementary material. For the video see: 

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

Dec 07, 2015
Nikolaus Mayer, Eddy Ilg, Philip Häusser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox

* Includes supplementary material 

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