Few-Shot Stereo Matching with High Domain Adaptability Based on Adaptive Recursive Network
Author:
Funder
Digital Finance CRC
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s11263-023-01953-0.pdf
Reference49 articles.
1. Cai, C., Poggi, M., Mattoccia, S., & Mordohai, P. (2020). Matching-space stereo networks for cross-domain generalization. In 2020 International conference on 3D vision (3DV) (pp. 364–373).
2. Calonder, M., Lepetit, V., Strecha, C., & Fua, P. (2010). BRIEF: Binary robust independent elementary features. In European Conference on computer vision-ECCV 2010 (pp. 778–792).
3. Chang, J.-R., & Chen, Y.-S. (2018). Pyramid stereo matching network. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 5410–5418).
4. Chang, T., Yang, X., Zhang, T., & Wang, M. (2023). Domain generalized stereo matching via hierarchical visual transformation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) (pp. 9559–9568).
5. Chen, Z., Sun, X., Wang, L., Yu, Y., & Huang, C. (2015). A deep visual correspondence embedding model for stereo matching costs. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 972–980).
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