WAFT-Stereo: Warping-Alone Field Transforms for Stereo Matching
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Acceso en línea: | |
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| _version_ | 1866908920072634368 |
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| author | Wang, Yihan Deng, Jia |
| author_facet | Wang, Yihan Deng, Jia |
| contents | We introduce WAFT-Stereo, a simple and effective warping-based method for stereo matching. WAFT-Stereo demonstrates that cost volumes, a common design used in many leading methods, are not necessary for strong performance and can be replaced by warping with improved efficiency. WAFT-Stereo ranks first on ETH3D (BP-0.5), Middlebury (RMSE), and KITTI (all metrics), reducing the zero-shot error by 81% on ETH3D, while being 1.8-6.7x faster than competitive methods. Code and model weights are available at https://github.com/princeton-vl/WAFT-Stereo. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_24836 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | WAFT-Stereo: Warping-Alone Field Transforms for Stereo Matching Wang, Yihan Deng, Jia Computer Vision and Pattern Recognition We introduce WAFT-Stereo, a simple and effective warping-based method for stereo matching. WAFT-Stereo demonstrates that cost volumes, a common design used in many leading methods, are not necessary for strong performance and can be replaced by warping with improved efficiency. WAFT-Stereo ranks first on ETH3D (BP-0.5), Middlebury (RMSE), and KITTI (all metrics), reducing the zero-shot error by 81% on ETH3D, while being 1.8-6.7x faster than competitive methods. Code and model weights are available at https://github.com/princeton-vl/WAFT-Stereo. |
| title | WAFT-Stereo: Warping-Alone Field Transforms for Stereo Matching |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2603.24836 |