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DrivingStereo
Stereo
Stereo Matching
|...
许可协议: MIT License

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}
}

License

This dataset is released under the MIT license.

数据概要
数据格式
image,
数据量
182.188K
文件大小
--
发布方
Guorun Yang
Guorun Yang is a Ph.D. Student of Tsinghua University
| 数据量 182.188K | 大小 --
DrivingStereo
Stereo
Stereo Matching
许可协议: MIT License

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}
}

License

This dataset is released under the MIT license.

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