OpenStereo is a flexible and extensible project for stereo matching.
- [Jan 28th, 2025]: The paper of LightStereo has been accepted by ICRA 2025.
- [Nov 22nd, 2024]: The paper of StereoAnything makes public: Stereo Anything: Unifying Stereo Matching with Large-Scale Mixed Data.
- [July 1st, 2024]: The paper of LightStereo makes public: LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation.
- [June 26th, 2024]: TensorRT has been integrated, please see the Deployment documentation.
- [May 2024]: The 2.0 version of OpenStereo is available, featuring an optimized training and testing framework.
- [January 2024]: Our proposed StereoBase rank 1st on the KITTI15 leaderboard!!!
- [December 2023]: Our paper makes public: OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline.
- [March 2023]:OpenStereo is available!!!
- [ICRA25] LightStereo: Channel Boost Is All Your Need for Efficient 2D Cost Aggregation, Paper and Code.
- [Arxiv'24] Stereo Anything: Unifying Stereo Matching with Large-Scale Mixed Data, Paper and ProjectPage
- [Arxiv'23] OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline, Paper and Code.
- Multiple Dataset supported: OpenStereo supports 15 popular stereo datasets: SceneFlow, KITTI12 & KITTI15, ETH3D, Middlebury, DrivingStereo, Sintel, FallingThings, InStereo2K,UnrealStereo4k, VirtualKitti2, CREStereo, Argoverse, Spring, and TartanAir.
- Multiple Models Support: We reproduced several SOTA methods and achieved the same or even better performance.
- DDP Support: The officially recommended
Distributed Data Parallel (DDP)mode is used during both the training and testing phases. - AMP Support: The
Auto Mixed Precision (AMP)option is available. - TensorRT Support: TensorRT has been integrated.
- Nice log: We use
tensorboardandloggingto log everything, which looks pretty.
Please see 0.get_started.md. We also provide the following tutorials for your reference:
Results and models are available in the model zoo.
AANet ACVNet CascadeStereo CFNet COEX DenseMatching FADNet++ GwcNet MSNet PSMNet RAFT STTR OpenGait IGEV NMRF
@article{OpenStereo,
title={OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline},
author={Guo, Xianda and Zhang, Chenming and Lu, Juntao and Wang, Yiqi and Duan, Yiqun and Yang, Tian and Zhu, Zheng and Chen, Long},
journal={arXiv preprint arXiv:2312.00343},
year={2023}
}
@article{guo2024stereo,
title={Stereo Anything: Unifying Stereo Matching with Large-Scale Mixed Data},
author={Guo, Xianda and Zhang, Chenming and Zhang, Youmin and Nie, Dujun and Wang, Ruilin and Zheng, Wenzhao and Poggi, Matteo and Chen, Long},
journal={arXiv preprint arXiv:2411.14053},
year={2024}
}
@inproceedings{guo2025lightstereo,
title={Lightstereo: Channel boost is all you need for efficient 2d cost aggregation},
author={Guo, Xianda and Zhang, Chenming and Nie, Dujun and Zheng, Wenzhao and Zhang, Youmin and Chen, Long},
booktitle={ICRA},
year={2025}
}
Note: This code is only used for academic purposes, people cannot use this code for anything that might be considered commercial use.