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DrivingStereo

A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios

DrivingStereo

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.

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Task
Autonomous Driving
Annotation Types
Bounding Boxes
182188
Items
5
Classes
182188
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Unknown
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