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DrivingStereo
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Overview

We construct a large-scale stereo dataset named DrivingStereo. It contains over 180k images covering a diverse set of driving scenarios, which is hundreds of times larger than the KITTI stereo dataset. High-quality labels of disparity are produced by a model-guided filtering strategy from multi-frame LiDAR points. Compared with other dataset, the deep-learning models trained on our DrivingStereo achieve higher generalization accuracy in real-world driving scenes. The details of our dataset are described in our paper.

Examples

Citation

Please use the following citation when referencing the dataset:

@inproceedings{yang2019drivingstereo
    title={DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios},
    author={Yang, Guorun and Song, Xiao and Huang, Chaoqin and Deng, Zhidong and Shi, Jianping
and Zhou, Bolei},
    booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2019}
}
数据集信息
应用场景Stereo Matching
标注类型Others
LicenseUnknown
更新时间2021-03-24 22:51:48
数据概要
数据格式Image
数据数量182.19k
已标注数量0
文件大小0B
版权归属方
Guorun Yang
标注方
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