Deformable Object Perception

Deformable Object Perception is the computational process of interpreting and reconstructing the time-varying geometry and pose of non-rigid entities from sensor data, distinguishing itself from rigid object perception by explicitly accounting for continuous shape changes due to external forces or internal dynamics.

33

Publications

1.9K

Citations

119

Authors

64

Institutions

Publications per year

2017–2026

15

Authors

119

  1. BX
    Bei Xiao

    American University, United States

    2 publications · 108 citations

    2

    h-index

  2. WB
    Wenyan Bi

    American University, United States

    2 publications · 108 citations

    2

    h-index

  3. AC
    Andrea Cherubini

    Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, France

    2 publications · 81 citations

    2

    h-index

  4. GA
    Gerardo Aragón-Camarasa

    University of Glasgow, United Kingdom

    1 publications · 19 citations

    1

    h-index

  5. XH
    Xuzhao Huang

    University of Hong Kong, Hong Kong SAR China

    1 publications · 26 citations

    1

    h-index

1–5 of 119

Venues

  1. Robotics and Autonomous Systems

    4 publications · 157 citations

    4

    h-index

  2. Frontiers in Computational Neuroscience

    2 publications · 123 citations

    2

    h-index

  3. Journal of Vision

    2 publications · 117 citations

    2

    h-index

  4. i-Perception

    1 publications · 58 citations

    1

    h-index

  5. Ecological Psychology

    1 publications · 23 citations

    1

    h-index

1–5