Affordance Detection
Affordance Detection is a computational perception framework that identifies actionable possibilities offered by objects or environments in a scene by integrating sensory inputs with semantic and geometric reasoning to determine how an agent can physically interact with them.
113
Publications
6.6K
Citations
308
Authors
140
Institutions
Publications per year
2017–2026
70
113
Affordance detection of tool parts from geometric features
Austin Myers, Ching L. Teo, Cornelia Fermüller et al. · 2015 · 278 citations
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University of Science and Technology of China
Hefei, China
7 h-index
25 publications
710 citations

The University of Sydney
Sydney, Australia
5 h-index
10 publications
581 citations
Google (United States)
Mountain View, United States
4 h-index
2 publications
72 citations
Stanford University
Stanford, United States
4 h-index
9 publications
579 citations

University of Edinburgh
Edinburgh, United Kingdom
4 h-index
4 publications
113 citations
Georgia Institute of Technology
Atlanta, United States
3 h-index
12 publications
581 citations

Universität Innsbruck
Innsbruck, Austria
3 h-index
7 publications
163 citations
Tsinghua University
Beijing, China
3 h-index
2 publications
55 citations
1–8 of 140
7 publications · 256 citations
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Repository · 6 publications · 143 citations
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4 publications · 213 citations
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2 publications · 602 citations
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Conference · 2 publications · 77 citations
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