Concepedia

Actionable Region Detection

Actionable Region Detection is a computational method in manipulation perception that identifies task-relevant spatial regions within sensor inputs to guide robotic interaction by distinguishing areas amenable to physical intervention from background or irrelevant context.

3

Publications

179

Citations

7

Authors

3

Institutions

Publications per year

2017–2026

1

Parents

Publications

3

1–3 of 3

Authors

7

  1. SS
    Stefano Soatto

    University of California, Los Angeles, United States

    2 publications · 64 citations

    2

    h-index

  2. ST
    Shubham Tulsiani

    Carnegie Mellon University, United States

    1 publications · 115 citations

    1

    h-index

  3. MM
    Mustafa Mukadam

    Georgia Institute of Technology, United States

    1 publications · 115 citations

    1

    h-index

  4. GG
    Georgios Georgiadis

    University of California, Los Angeles, United States

    1 publications · 11 citations

    1

    h-index

  5. LG
    Leonidas Guibas

    Stanford University, United States

    1 publications · 115 citations

    1

    h-index

1–5 of 7

Institutions

3

  1. University of California, Los Angeles

    Los Angeles, United States

    2 h-index

    3 publications

    75 citations

  2. Stanford University

    Stanford, United States

    1 h-index

    2 publications

    230 citations

  3. Meta (Israel)

    Tel Aviv, Israel

    1 h-index

    3 publications

    345 citations

1–3 of 3

Venues

  1. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 1 publications · 115 citations

    1

    h-index

1–1