Spatial Graph Representation
Spatial Graph Representation is a formal method for modeling spatial knowledge by structuring entities and their relationships as a graph, where nodes represent spatial entities and edges encode topological, geometric, or semantic relations among them.
90
Publications
6.1K
Citations
261
Authors
151
Institutions
Publications per year
2017–2026
48
90
Skeleton-Based Action Recognition With Shift Graph Convolutional Network
Ke Cheng, Yifan Zhang, Xiangyu He et al. · 2020 · 948 citations
SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction
Liushuai Shi, Le Wang, Chengjiang Long et al. · 2021 · 314 citations
1–5 of 90
261
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1–5 of 261
151

Chinese Academy of Sciences
Beijing, China
5 h-index
17 publications
6.8K citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
16 publications
7K citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
8 publications
229 citations
Waseda University
Tokyo, Japan
2 h-index
3 publications
31 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
4 publications
111 citations

Tulane University
New Orleans, United States
2 h-index
2 publications
86 citations
Nanjing University of Science and Technology
Nanjing, China
2 h-index
8 publications
240 citations

University of Alberta
Edmonton, Canada
2 h-index
2 publications
58 citations
1–8 of 151
Repository · 5 publications · 149 citations
5
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Conference · 5 publications · 992 citations
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TPAMI · 3 publications · 125 citations
3
h-index
JASIS · 2 publications · 86 citations
2
h-index
2 publications · 34 citations
2
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1–5