driving__optical_flow.tar.bz2 53.08GB
Type: Dataset

Metadata:
@article{,
title= {driving__optical_flow.tar.bz2},
keywords= {disparity,scene flow,optical flow,dataset,synthetic},
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 "Optical Flow" data 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superseded= {},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}
}

Citation:
Mayer, N., Ilg, E., Hausser, P., Fischer, P., Cremers, D., Dosovitskiy, A., & Brox, T.. (2018). driving__optical_flow.tar.bz2 [Data set]. Academic Torrents. https://academictorrents.com/details/f0eea7805f4174265b60ccc26be05eee979d0896
10 day statistics (2 downloads)
Average Time 29 mins, 59 secs
Average Speed 29.50MB/s
Best Time 29 mins, 59 secs
Best Speed 29.50MB/s
Worst Time 30 mins, 00 secs
Worst Speed 29.49MB/s

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