Graph matching and edit distance algorithms form a cornerstone of modern computational techniques used to quantify the similarity between structured data. These methods underpin a wide array of ...
为解决图像关键点匹配中因遮挡、视角变化导致的噪声对应问题，研究团队提出首个基于元学习的Meta Matching Correction for noisy Graph Matching(MCGM)框架。通过Meta Correcting Network(MCN)融合全局特征与几何一致性信息生成置信度评分，采用双层优化实现动态校正。实验表明 ...
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