Adaptive Assignment for Geometry Aware Local Feature Matching

• URL: http://arxiv.org/abs/2207.08427v3
• Date: Wed, 29 Mar 2023 02:47:13 GMT
• Title: Adaptive Assignment for Geometry Aware Local Feature Matching
• Authors: Dihe Huang, Ying Chen, Shang Xu, Yong Liu, Wenlong Wu, Yikang Ding, Chengjie Wang, Fan Tang
• Abstract summary: detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance. We introduce AdaMatcher, which accomplishes the feature correlation and co-visible area estimation through an elaborate feature interaction module. AdaMatcher then performs adaptive assignment on patch-level matching while estimating the scales between images, and finally refines the co-visible matches through scale alignment and sub-pixel regression module.
• Score: 22.818457285745733
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance. However, these methods still struggle at large-scale and viewpoint variations, due to the geometric inconsistency resulting from the application of the mutual nearest neighbour criterion (\ie, one-to-one assignment) in patch-level matching.Accordingly, we introduce AdaMatcher, which first accomplishes the feature correlation and co-visible area estimation through an elaborate feature interaction module, then performs adaptive assignment on patch-level matching while estimating the scales between images, and finally refines the co-visible matches through scale alignment and sub-pixel regression module.Extensive experiments show that AdaMatcher outperforms solid baselines and achieves state-of-the-art results on many downstream tasks. Additionally, the adaptive assignment and sub-pixel refinement module can be used as a refinement network for other matching methods, such as SuperGlue, to boost their performance further. The code will be publicly available at https://github.com/AbyssGaze/AdaMatcher.

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