Abstract:
This torrent contains the "Clean pass" images (WebP format) for the "Driving" dataset from the CVPR 2016 paper "A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation" by Mayer et al. (https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html).

URL: https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html
License: No license specified, the work may be protected by copyright.

Terms: https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html#tou

@article{,
title= {driving__frames_cleanpass_webp.tar},
keywords= {Dataset, synthetic, disparity, scene flow},
journal= {},
author= {Nikolaus Mayer and Eddy Ilg and Philip Hausser and Philipp Fischer and Daniel Cremers and Alexey Dosovitskiy and Thomas Brox},
year= {},
url= {https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html},
license= {},
abstract= {This torrent contains the "Clean pass" images (WebP format) for the "Driving" dataset from the CVPR 2016 paper "A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation" by Mayer et al. (https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html).},
superseded= {},
terms= {https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html#tou}
}