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MPI Sintel Stereo Training
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c77d1cf9-8cd1-11eb-88ae-0e1f58d5e9a9
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Jun 20, 2021 7:38 AM
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Overview

Ground truth optical flow is difficult to measure in real scenes with natural motion. As a result, optical flow data sets are restricted in terms of size, complexity, and diversity, making optical flow algorithms difficult to train and test on realistic data. We introduce a new optical flow data set derived from the open source 3D animated short film Sintel. This data set has important features not present in the popular Middlebury flow evaluation: long sequences, large motions, specular reflections, motion blur, defocus blur, and atmospheric effects.

Citation

Please use the following citation when referencing the dataset:

@inproceedings{Butler:ECCV:2012,
title = {A naturalistic open source movie for optical flow evaluation},
author = {Butler, D. J. and Wulff, J. and Stanley, G. B. and Black, M. J.},
booktitle = {European Conf. on Computer Vision (ECCV)},
editor = {{A. Fitzgibbon et al. (Eds.)}},
publisher = {Springer-Verlag},
series = {Part IV, LNCS 7577},
month = oct,
pages = {611--625},
year = {2012}
}
🎉Many thanks to Graviti Open Datasets for contributing the dataset
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Updated on2021-01-20 04:34:14
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Copyright Owner
Daniel J. Butler
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Unknown