Self-supervised Depth Estimation

Self-Supervised Depth Estimation is a methodological framework within depth estimation that leverages unlabeled monocular video sequences to learn depth and camera pose through image reconstruction consistency, without requiring explicit ground-truth depth annotations.

256

Publications

12.2K

Citations

769

Authors

213

Institutions

Publications per year

2017–2026

255

Authors

769

  1. MP
    Matteo Poggi

    University of Bologna, Italy

    9 publications · 644 citations

    11

    h-index

  2. FT
    Fabio Tosi

    University of Bologna, Italy

    8 publications · 595 citations

    10

    h-index

  3. SM
    Stefano Mattoccia

    University of Bologna, Italy

    9 publications · 644 citations

    10

    h-index

  4. AG
    Adrien Gaidon

    Toyota Research Institute

    9 publications · 469 citations

    9

    h-index

  5. VG
    Vitor Guizilini

    The University of Sydney, Australia

    9 publications · 469 citations

    9

    h-index

1–5 of 769

Venues

  1. arXiv (Cornell University)

    Repository · 38 publications · 1.3K citations

    21

    h-index

  2. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 13 publications · 978 citations

    13

    h-index

  3. IEEE Robotics and Automation Letters

    11 publications · 541 citations

    13

    h-index

  4. 8

    h-index

  5. 7

    h-index

1–5