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DrivingStereo
Others
Stereo Matching
|...
License: Unknown

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}
}
Data Summary
Type
Image,
Amount
182.188K
Size
--
Provided by
Guorun Yang
Guorun Yang is a Ph.D. Student of Tsinghua University
| Amount 182.188K | Size --
DrivingStereo
Others
Stereo Matching
License: Unknown

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}
}
0
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