Cross-view Localization
Cross-View Localization is a landmark-based localization method that determines the position and orientation of a query image by matching it across distinct visual viewpoints, typically between ground-level and aerial or satellite imagery, differing from other localization approaches in its explicit handling of large viewpoint disparities through view-invariant feature representation.
59
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4.5K
Citations
139
Authors
52
Institutions
Publications per year
2017–2026
54
Variants
Cross-view Geo-localization
Parents
59
Learning deep representations for ground-to-aerial geolocalization
Tsung-Yi Lin, Yin Cui, Serge Belongie et al. · 2015 · 409 citations
CVM-Net: Cross-View Matching Network for Image-Based Ground-to-Aerial Geo-Localization
Sixing Hu, Mengdan Feng, Rang Nguyen et al. · 2018 · 368 citations
Lending Orientation to Neural Networks for Cross-View Geo-Localization
Liu Liu, Hongdong Li · 2019 · 302 citations
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Australian National University
Canberra, Australia
7 h-index
22 publications
2K citations
Wuhan University
Wuhan, China
4 h-index
1 publications
47 citations
China Jiliang University
Hangzhou, China
3 h-index
12 publications
1.2K citations

University of North Carolina at Charlotte
Charlotte, United States
3 h-index
10 publications
973 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
7 publications
542 citations
Hangzhou Dianzi University
Hangzhou, China
3 h-index
9 publications
1.4K citations

Shenzhen University
Shenzhen, China
2 h-index
7 publications
209 citations

Chongqing University
Chongqing, China
2 h-index
1 publications
154 citations
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4 publications · 124 citations
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Repository · 5 publications · 58 citations
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4 publications · 698 citations
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4 publications · 141 citations
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Conference · 2 publications · 174 citations
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