Multi-view Depth Estimation

Multi-View Depth Estimation is a computational method in computer vision that infers depth information for a scene by jointly analyzing multiple images captured from distinct but overlapping viewpoints, leveraging geometric correspondences and photometric consistency across views.

226

Publications

20.9K

Citations

713

Authors

246

Institutions

Publications per year

2017–2026

150

Authors

713

  1. RR
    Ravi Ramamoorthi

    University of California, Berkeley, United States

    8 publications · 1.8K citations

    8

    h-index

  2. ML
    Miaomiao Liu

    Australian National University, Australia

    5 publications · 508 citations

    5

    h-index

  3. MP
    Marc Pollefeys

    ETH Zurich, Switzerland

    5 publications · 199 citations

    5

    h-index

  4. JY
    Jiayu Yang

    Australian National University, Australia

    5 publications · 508 citations

    5

    h-index

  5. TF
    Toshiaki Fujii

    Nagoya University, Japan

    5 publications · 440 citations

    5

    h-index

1–5 of 713

Venues

  1. arXiv (Cornell University)

    Repository · 25 publications · 950 citations

    18

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 12 publications · 2.8K citations

    11

    h-index

  3. IEEE Transactions on Image Processing

    11 publications · 407 citations

    11

    h-index

  4. 8

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 7 publications · 1.1K citations

    7

    h-index

1–5