Cross-view Image Retrieval
Cross-View Image Retrieval is a type of image retrieval task that involves matching images across different views or modalities, such as aerial to ground-level, satellite to map, or 3D to 2D representations, where the distinguishing characteristic is the significant geometric and appearance discrepancy between the source and target views.
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36
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2017–2026
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Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval
Li Liu, Fumin Shen, Yuming Shen et al. · 2017 · 280 citations
VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval
Sijie Zhu, Taojiannan Yang, Chen Chen · 2021 · 196 citations
Kuan-Hsien Liu, Ting-Yen Chen, Chu‐Song Chen · 2016 · 99 citations
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University of Electronic Science and Technology of China
Chengdu, China
3 h-index
5 publications
710 citations
Tianjin University
Tianjin, China
3 h-index
13 publications
344 citations

Beihang University
Beijing, China
2 h-index
2 publications
305 citations
Wuhan University
Wuhan, China
2 h-index
3 publications
143 citations

University of East Anglia
Norwich, United Kingdom
2 h-index
6 publications
915 citations
Michigan State University
East Lansing, United States
1 h-index
1 publications
1.6K citations
State Key Laboratory of Industrial Control Technology
Hangzhou, China
1 h-index
5 publications
140 citations

Australian National University
Canberra, Australia
1 h-index
2 publications
170 citations
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2 publications · 163 citations
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2 publications · 82 citations
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Repository · 2 publications · 42 citations
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1 publications · 21 citations
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1 publications · 23 citations
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