Type: Dataset
Tags: Dataset, optical flow, synthetic, disparity, scene flow

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superseded= {},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}

10 day statistics (3 downloads)

Average Time 13 mins, 22 secs
Average Speed 11.92MB/s
Best Time 2 mins, 53 secs
Best Speed 55.27MB/s
Worst Time 34 mins, 15 secs
Worst Speed 4.65MB/s