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superseded= {},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 38 minutes, 25 seconds
Average Speed 4.15MB/s
Best Time 5 minutes, 05 seconds
Best Speed 31.35MB/s
Worst Time 2 hours, 23 minutes, 23 seconds
Worst Speed 1.11MB/s
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