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arXiv Computer Vision By Zhiyang Li, Ruijiang Jin, Thibaut Klenke, Yusuke Sekikawa, Nakamasa Inoue

WovenAnchor Matcher: Specialized Intra- and Inter-Image Context Modeling for Feature Matching

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The paper introduces WovenAnchor Matcher (WAM), a semi‑dense feature matching framework that separates intra‑image and inter‑image context aggregation. WAM uses WovenMamba for horizontal‑then‑vertical state‑space propagation to preserve structured 2D dependencies within each image, and AnchorCrossAttention to gather context from plausible corresponding regions across image pairs via cross‑attention over local anchors. Experiments on MegaDepth show WAM achieving 66.1 pose AUC@5°, a 2.0‑point improvement over the JamMa baseline, and ablations confirm the necessity of both specialized components.

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