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superseded= {},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 (7 downloads)

Average Time 3 hrs, 29 mins, 39 secs
Average Speed 531.17kB/s
Best Time 0 mins, 52 secs
Best Speed 128.50MB/s
Worst Time 21 hrs, 49 mins, 01 secs
Worst Speed 85.08kB/s