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Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence.

, , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (7): 8159-8175 (July 2023)

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Transferring Knowledge to Smaller Network with Class-Distance Loss., and . ICLR (Workshop), OpenReview.net, (2017)Data-driven dementia diagnosis record visualization system., , , , , and . VINCI, page 75-76. ACM, (2017)Multi-view Image Prompted Multi-view Diffusion for Improved 3D Generation., , , , and . CoRR, (2024)TransforMatcher: Match-to-Match Attention for Semantic Correspondence., , and . CVPR, page 8687-8697. IEEE, (2022)Learning to Distill Convolutional Features into Compact Local Descriptors., , , , and . WACV, page 897-907. IEEE, (2021)Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 16787-16806. PMLR, (2023)Learning Rotation-Equivariant Features for Visual Correspondence., , , and . CVPR, page 21887-21897. IEEE, (2023)Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks., , and . MICCAI (1), volume 11070 of Lecture Notes in Computer Science, page 520-528. Springer, (2018)Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence., , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (7): 8159-8175 (July 2023)Efficient Semantic Matching with Hypercolumn Correlation., , and . WACV, page 138-147. IEEE, (2024)