Affordance Learning
Affordance Learning is a robotic learning framework that identifies and models the possible interactions between an agent and objects in its environment based on sensorimotor data, distinguishing itself by enabling action prediction and selection through perception of environmental affordances without requiring explicit supervision.
203
Publications
12.1K
Citations
544
Authors
231
Institutions
Publications per year
2017–2026
79
203
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
Chenyi Chen, Ari Seff, Alain L. Kornhauser et al. · 2015 · 1.8K citations
1–5 of 203
544
14
h-index
13
h-index
10
h-index
9
h-index
8
h-index
1–5 of 544
231
Middle East Technical University
Ankara, Türkiye
12 h-index
28 publications
1.1K citations
Georgia Institute of Technology
Atlanta, United States
10 h-index
29 publications
1.1K citations
Instituto Superior Técnico
Lisbon, Portugal
9 h-index
26 publications
2.6K citations

Italian Institute of Technology
Genoa, Italy
8 h-index
25 publications
816 citations

Universität Innsbruck
Innsbruck, Austria
8 h-index
18 publications
699 citations
Carnegie Mellon University
Pittsburgh, United States
7 h-index
15 publications
860 citations
Instituto de Engenharia de Sistemas e Computadores Microsistemas e Nanotecnologias
Lisbon, Portugal
6 h-index
20 publications
2K citations
University of Lisbon
Lisbon, Portugal
6 h-index
20 publications
455 citations
1–8 of 231
Repository · 12 publications · 407 citations
12
h-index
TCDS · 4 publications · 163 citations
4
h-index
4 publications · 269 citations
4
h-index
3 publications · 183 citations
3
h-index
Conference · 3 publications · 159 citations
3
h-index
1–5