Multi-object Tracking

Multi-Object Tracking is a computer vision framework that extends visual tracking by simultaneously localizing and maintaining the identities of multiple objects across video frames, distinguishing itself from single-object tracking and detection through its focus on identity association and motion coherence in cluttered, dynamic scenes.

1.9K

Publications

132.1K

Citations

4.8K

Authors

1.3K

Institutions

Publications per year

2017–2026

971

Authors

4.8K

  1. LL
    Laura Leal-Taixé

    Technical University of Munich, Germany

    26 publications · 5.6K citations

    22

    h-index

  2. BV
    Ba‐Ngu Vo

    Curtin University, Australia

    22 publications · 2K citations

    20

    h-index

  3. KS
    Konrad Schindler

    ETH Zurich, Switzerland

    21 publications · 7.2K citations

    19

    h-index

  4. BV
    Ba-Tuong Vo

    Curtin University, Australia

    18 publications · 1.7K citations

    17

    h-index

  5. IR
    Ian Reid

    The University of Adelaide, Australia

    18 publications · 4K citations

    17

    h-index

1–5 of 4.8K

Venues

  1. arXiv (Cornell University)

    Repository · 119 publications · 8.1K citations

    37

    h-index

  2. 32

    h-index

  3. 24

    h-index

  4. Sensors

    39 publications · 1.4K citations

    22

    h-index

  5. IEEE Transactions on Image Processing

    25 publications · 1.7K citations

    21

    h-index

1–5