Feature Correspondence Analysis
Feature Correspondence Analysis is a methodological framework in computer vision and pattern recognition that establishes precise mappings between distinctive attributes or landmarks in paired or multi-view feature spaces to enable cross-domain, cross-modal, or cross-temporal data alignment.
161
Publications
7.1K
Citations
537
Authors
254
Institutions
Publications per year
2017–2026
37
Parents
161
Learning to Parse Wireframes in Images of Man-Made Environments
Kun Huang, Yifan Wang, Zihan Zhou et al. · 2018 · 232 citations
1–5 of 161
537
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Institut national de recherche en sciences et technologies du numérique, France
3 publications · 503 citations
3
h-index
Institut national de recherche en sciences et technologies du numérique, France
3 publications · 503 citations
3
h-index
Institut national de recherche en sciences et technologies du numérique, France
3 publications · 503 citations
3
h-index
1–5 of 537
254
Florida International University
Miami, United States
7 h-index
11 publications
252 citations
University of Miami
Coral Gables, United States
6 h-index
14 publications
480 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
9 publications
520 citations

McGill University
Montreal, Canada
3 h-index
7 publications
424 citations

Huazhong University of Science and Technology
Wuhan, China
3 h-index
7 publications
183 citations
University of Oxford
Oxford, United Kingdom
3 h-index
4 publications
1.4K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
3 h-index
7 publications
795 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
3 h-index
3 publications
503 citations
1–8 of 254
5 publications · 223 citations
5
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Repository · 5 publications · 124 citations
5
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TPAMI · 3 publications · 598 citations
3
h-index
3 publications · 104 citations
3
h-index
Repository · 3 publications · 124 citations
3
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1–5