driving__frames_finalpass.tar6.55GB
Type: Dataset
Tags:Dataset, disparity, scene flow, synthetic, optical flow

Bibtex:
@article{,
title= {driving__frames_finalpass.tar},
keywords= {Dataset, optical flow, 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 "Final 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superseded= {},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}
}


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Average Time 2 hours, 00 minutes, 34 seconds
Average Speed 905.19kB/s
Best Time 1 hours, 49 minutes, 49 seconds
Best Speed 993.87kB/s
Worst Time 2 hours, 11 minutes, 20 seconds
Worst Speed 831.04kB/s
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