Spatial Feature Fusion
Spatial Feature Fusion is a geospatial data integration methodology that combines multiple spatially referenced feature representations through rule-based or learned transformation rules to generate a unified, semantically enhanced feature space while preserving topological fidelity across disparate geographic scales and modalities.
237
Publications
10.4K
Citations
934
Authors
292
Institutions
Publications per year
2017–2026
216
237
Flowing ConvNets for Human Pose Estimation in Videos
Tomas Pfister, James Charles, Andrew Zisserman · 2015 · 512 citations
Learning Spatial Fusion for Single-Shot Object Detection
Songtao Liu, Di Huang, Yunhong Wang · arXiv (Cornell University) · 2019 · 468 citations · Full text
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292

Chinese Academy of Sciences
Beijing, China
13 h-index
26 publications
919 citations

Zhejiang University
Hangzhou, China
11 h-index
22 publications
1.6K citations

Central South University
Changsha, China
7 h-index
25 publications
1.2K citations

Shanghai Jiao Tong University
Shanghai, China
6 h-index
29 publications
818 citations
China University of Geosciences
Wuhan, China
6 h-index
13 publications
411 citations
University of Chinese Academy of Sciences
Beijing, China
6 h-index
11 publications
353 citations
Wuhan University
Wuhan, China
6 h-index
23 publications
1.9K citations
Jiangsu University
Zhenjiang, China
5 h-index
13 publications
1K citations
1–8 of 292
15 publications · 564 citations
14
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11 publications · 365 citations
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7 publications · 463 citations
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8 publications · 228 citations
9
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4 publications · 138 citations
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