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MPI Sintel Stereo Training
创建来自Hello Dataset / Robert
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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}
}
数据集信息
应用场景Stereo Matching
标注类型Disparity
LicenseUnknown
更新时间2021-03-24 22:54:04
数据概要
数据格式Image
数据数量0
文件大小2MB
标注数量0
版权归属方
Daniel J. Butler
标注方
未知
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