Multi-task Depth Estimation

Multi-Task Depth Estimation is a computational framework within depth estimation that jointly learns depth prediction alongside one or more related auxiliary tasks to improve feature representation and overall estimation accuracy through shared learning.

55

Publications

3.9K

Citations

223

Authors

85

Institutions

Publications per year

2017–2026

51

Authors

223

  1. IR
    Ian Reid

    The University of Adelaide, Australia

    3 publications · 433 citations

    3

    h-index

  2. AG
    Adrien Gaidon

    Toyota Research Institute

    3 publications · 210 citations

    3

    h-index

  3. CS
    Chunhua Shen

    The University of Adelaide, Australia

    3 publications · 433 citations

    3

    h-index

  4. RA
    Rareş Ambruş

    Toyota Research Institute

    3 publications · 210 citations

    3

    h-index

  5. VG
    Vitor Guizilini

    The University of Sydney, Australia

    3 publications · 210 citations

    3

    h-index

1–5 of 223

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 844 citations

    10

    h-index

  2. 3

    h-index

  3. 3

    h-index

  4. 2

    h-index

  5. IEEE Robotics and Automation Letters

    2 publications · 112 citations

    2

    h-index

1–5