3D Object Detection Fusion

3D Object Detection Fusion is a methodological framework within object detection fusion that integrates complementary spatial and semantic information from multiple sensors or modalities to jointly infer the precise three-dimensional location, orientation, and class of objects in a scene.

205

Publications

21.5K

Citations

770

Authors

215

Institutions

Publications per year

2017–2026

202

Authors

770

  1. JN
    Jiquan Ngiam

    Google (United States), United States

    6 publications · 4K citations

    7

    h-index

  2. JW
    Jun Won Choi

    Hanyang University, South Korea

    5 publications · 333 citations

    6

    h-index

  3. DK
    Dongsuk Kum

    Korea Advanced Institute of Science and Technology, South Korea

    5 publications · 333 citations

    6

    h-index

  4. VV
    Vijay Vasudevan

    Google (United States), United States

    4 publications · 3.4K citations

    5

    h-index

  5. DA
    Dragomir Anguelov

    Google (United States), United States

    4 publications · 3.4K citations

    5

    h-index

1–5 of 770

Venues

  1. arXiv (Cornell University)

    Repository · 28 publications · 1.9K citations

    19

    h-index

  2. Sensors

    8 publications · 229 citations

    10

    h-index

  3. 9

    h-index

  4. 7

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 7 publications · 538 citations

    7

    h-index

1–5