Object Affordance Detection

Object Affordance Detection is a computational method that identifies the set of actions or functions an object enables in a given context, distinguished from related perception tasks by its focus on extracting functionally relevant properties that specify potential interactions between agents and objects.

61

Publications

4.9K

Citations

166

Authors

87

Institutions

Publications per year

2017–2026

35

Authors

166

  1. YC
    Yang Cao

    University of Science and Technology of China, China

    6 publications · 184 citations

    6

    h-index

  2. WZ
    Wei Zhai

    University of Science and Technology of China, China

    5 publications · 150 citations

    5

    h-index

  3. HL
    Hongchen Luo

    University of Science and Technology of China, China

    5 publications · 150 citations

    5

    h-index

  4. DT
    Dacheng Tao

    The University of Sydney, Australia

    4 publications · 220 citations

    4

    h-index

  5. AN
    Anh‐Tu Nguyen

    Centre National de la Recherche Scientifique, France

    4 publications · 659 citations

    4

    h-index

1–5 of 166

Venues

  1. IEEE Robotics and Automation Letters

    4 publications · 150 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 83 citations

    3

    h-index

  3. IEEE Transactions on Cognitive and Developmental Systems

    TCDS · 2 publications · 68 citations

    2

    h-index

  4. 2

    h-index

  5. Autonomous Robots

    2 publications · 119 citations

    2

    h-index

1–5