driving__disparity.tar.bz29.56GB
Type: Dataset
Tags:Dataset, optical flow, synthetic, disparity, scene flow

Bibtex:
@article{,
title= {driving__disparity.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 "Disparity" 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superseded= {},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}
}


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10 day statistics (7 downloads taking more than 30 seconds)

Average Time 3 hours, 29 minutes, 30 seconds
Average Speed 760.62kB/s
Best Time 5 minutes, 31 seconds
Best Speed 28.89MB/s
Worst Time 14 hours, 00 minutes, 21 seconds
Worst Speed 189.63kB/s
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