Point Cloud Object Detection

Point Cloud Object Detection is a computational task in 3D computer vision that identifies and localizes instances of objects within a point cloud by assigning class labels and spatial bounding volumes to coherent groups of points.

532

Publications

56.9K

Citations

1.7K

Authors

488

Institutions

Publications per year

2017–2026

466

Authors

1.7K

  1. HL
    Hongsheng Li

    Chinese University of Hong Kong, Hong Kong SAR China

    14 publications · 7.6K citations

    14

    h-index

  2. SS
    Shaoshuai Shi

    Chinese University of Hong Kong, Hong Kong SAR China

    13 publications · 7.7K citations

    13

    h-index

  3. XW
    Xiaogang Wang

    European Organization for Nuclear Research, Switzerland

    11 publications · 7.3K citations

    11

    h-index

  4. DA
    Dragomir Anguelov

    Google (United States), United States

    6 publications · 1.3K citations

    9

    h-index

  5. YZ
    Yin Zhou

    Chongqing Jiaotong University, China

    7 publications · 5.2K citations

    9

    h-index

1–5 of 1.7K

Venues

  1. arXiv (Cornell University)

    Repository · 62 publications · 3.6K citations

    29

    h-index

  2. 17

    h-index

  3. Sensors

    16 publications · 4K citations

    15

    h-index

  4. 13

    h-index

  5. Remote Sensing

    11 publications · 316 citations

    12

    h-index

1–5