Patch-based Matching
Patch-Based Matching is a template matching approach that identifies occurrences of a target pattern by comparing localized image regions or data patches against a reference template through similarity measures, distinguishing itself by operating on discretely sampled subregions rather than global image structures.
122
Publications
13.9K
Citations
421
Authors
190
Institutions
Publications per year
2017–2026
54
Variants
Patch Matching
Parents
122
Connelly Barnes, Eli Shechtman, Adam Finkelstein et al. · ACM Transactions on Graphics · 2009 · 2.9K citations
Unsupervised Salience Learning for Person Re-identification
Rui Zhao, Wanli Ouyang, Xiaogang Wang · 2013 · 1K citations
MatchNet: Unifying feature and metric learning for patch-based matching
Xufeng Han, Thomas Leung, Yangqing Jia et al. · 2015 · 879 citations
Zezhou Cheng, Qingxiong Yang, Bin Sheng · 2015 · 557 citations
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190
Tsinghua University
Beijing, China
7 h-index
12 publications
567 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
14 publications
871 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
9 publications
267 citations

Shanghai Jiao Tong University
Shanghai, China
5 h-index
14 publications
1.5K citations
Korea University
Seoul, South Korea
4 h-index
6 publications
123 citations
Wuhan University
Wuhan, China
4 h-index
15 publications
691 citations
Harvard University
Cambridge, United States
4 h-index
6 publications
281 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
3 h-index
9 publications
5.2K citations
1–8 of 190
4 publications · 113 citations
4
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4 publications · 334 citations
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TPAMI · 3 publications · 317 citations
3
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TOG · 3 publications · 5.3K citations
3
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3 publications · 39 citations
3
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1–5