23 citations · 29 across the 8 of their papers we have counts for
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cs.CV2024★ 1 cited
MESA: Effective Matching Redundancy Reduction by Semantic Area Segmentation
Yesheng Zhang, Shuhan Shen, Xu Zhao
We propose MESA and DMESA as novel feature matching methods, which utilize Segment Anything Model (SAM) to effectively mitigate matching redundancy. The key insight of our methods…
cs.CV2024
MESA: Matching Everything by Segmenting Anything
Yesheng Zhang, Xu Zhao
Feature matching is a crucial task in the field of computer vision, which involves finding correspondences between images. Previous studies achieve remarkable performance using lea…