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

title= {driving__frames_cleanpass.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 (PNG 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superseded= {},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}

10 day statistics (17 downloads)

Average Time 33 mins, 26 secs
Average Speed 3.33MB/s
Best Time 5 mins, 05 secs
Best Speed 21.91MB/s
Worst Time 3 hrs, 18 mins, 21 secs
Worst Speed 561.46kB/s