Visual Relationship Detection
Visual Relationship Detection is a computational task in computer vision that identifies and classifies structured triplet relationships—comprising a subject, predicate, and object—within an image, distinguishing it from general object detection by explicitly modeling semantic interactions between visual entities.
205
Publications
24.2K
Citations
638
Authors
213
Institutions
Publications per year
2017–2026
170
205
Image-Based Recommendations on Styles and Substitutes
Julian McAuley, Christopher Targett, Qinfeng Shi et al. · 2015 · 2.3K citations
1–5 of 205
638
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University of Electronic Science and Technology of China, China
5 publications · 262 citations
5
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5
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1–5 of 638
213
National University of Singapore
Singapore, Singapore
13 h-index
39 publications
2.7K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
22 publications
1.5K citations
University of Science and Technology of China
Hefei, China
8 h-index
15 publications
381 citations
University of Washington
Seattle, United States
7 h-index
7 publications
346 citations

University of Electronic Science and Technology of China
Chengdu, China
7 h-index
26 publications
1.4K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
7 h-index
21 publications
3.4K citations

The University of Sydney
Sydney, Australia
5 h-index
6 publications
732 citations
Columbia University
New York, United States
5 h-index
8 publications
1.7K citations
1–8 of 213
Repository · 37 publications · 3.6K citations
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Conference · 8 publications · 468 citations
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6 publications · 493 citations
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4 publications · 271 citations
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TPAMI · 5 publications · 545 citations
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