Scene Hierarchy Learning
Scene Hierarchy Learning is a machine learning framework within scene classification that explicitly models hierarchical relationships among scene categories to improve contextual understanding and classification accuracy by leveraging multi-level semantic structures.
22
Publications
1.9K
Citations
68
Authors
32
Institutions
Publications per year
2017–2026
6
Parents
22
Learning hierarchical models of scenes, objects, and parts
Erik B. Sudderth, Antonio Torralba, William T. Freeman et al. · 2005 · 302 citations
Manyi Li, Akshay Gadi Patil, Kai Xu et al. · ACM Transactions on Graphics · 2019 · 190 citations
Understanding Indoor Scenes Using 3D Geometric Phrases
Wongun Choi, Yu-Wei Chao, Caroline Pantofaru et al. · 2013 · 189 citations
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32
Princeton University
Princeton, United States
4 h-index
11 publications
1.8K citations
University of California, Los Angeles
Los Angeles, United States
3 h-index
9 publications
504 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
3 publications
76 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
8 publications
1.4K citations

National University of Defense Technology
Changsha, China
2 h-index
3 publications
250 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
6 publications
678 citations
Simon Fraser University
Burnaby, Canada
2 h-index
4 publications
440 citations

Cornell University
Ithaca, United States
2 h-index
2 publications
101 citations
1–8 of 32
Conference · 3 publications · 558 citations
3
h-index
2 publications · 258 citations
2
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TOG · 2 publications · 259 citations
2
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Repository · 2 publications · 92 citations
2
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IJIG · 1 publications · 14 citations
1
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1–5