Multi-task Learning For Computer Vision

Multi-Task Learning for Computer Vision is a machine learning framework that jointly optimizes multiple visual recognition tasks within a shared architecture to improve generalization by leveraging commonalities and complementarities among the tasks.

495

Publications

49.1K

Citations

1.8K

Authors

503

Institutions

Publications per year

2017–2026

407

Authors

1.8K

  1. XW
    Xiaogang Wang

    European Organization for Nuclear Research, Switzerland

    6 publications · 973 citations

    6

    h-index

  2. YY
    Yan Yan

    University of Trento, Italy

    5 publications · 333 citations

    5

    h-index

  3. ER
    Elisa Ricci

    Fondazione Bruno Kessler, Italy

    5 publications · 333 citations

    5

    h-index

  4. AZ
    Amir Zamir

    Stanford University, United States

    4 publications · 481 citations

    5

    h-index

  5. JZ
    Jianguo Zhang

    University of Dundee, United Kingdom

    5 publications · 1.1K citations

    5

    h-index

1–5 of 1.8K

Venues

  1. arXiv (Cornell University)

    Repository · 71 publications · 8.6K citations

    30

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 14 publications · 2.8K citations

    14

    h-index

  3. IEEE Access

    13 publications · 530 citations

    13

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 12 publications · 911 citations

    13

    h-index

  5. Pattern Recognition

    10 publications · 410 citations

    11

    h-index

1–5