Dense Depth Estimation

Dense Depth Estimation is a depth estimation method that generates a depth value for every pixel in an image, distinguishing itself from sparse approaches by providing a complete, high-resolution depth map of the scene.

426

Publications

33.5K

Citations

1.3K

Authors

412

Institutions

Publications per year

2017–2026

255

Authors

1.3K

  1. AW
    Alex Wong

    University of California, Los Angeles, United States

    7 publications · 502 citations

    7

    h-index

  2. YD
    Yuchao Dai

    Northwestern Polytechnical University, China

    7 publications · 392 citations

    7

    h-index

  3. TK
    Takeo Kanade

    Carnegie Mellon University, United States

    7 publications · 790 citations

    7

    h-index

  4. SS
    Stefano Soatto

    University of California, Los Angeles, United States

    7 publications · 502 citations

    7

    h-index

  5. GZ
    Guofeng Zhang

    Zhejiang University, China

    5 publications · 568 citations

    5

    h-index

1–5 of 1.3K

Venues

  1. arXiv (Cornell University)

    Repository · 36 publications · 1.4K citations

    22

    h-index

  2. IEEE Transactions on Image Processing

    15 publications · 804 citations

    15

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 17 publications · 4.6K citations

    15

    h-index

  4. IEEE Robotics and Automation Letters

    12 publications · 463 citations

    11

    h-index

  5. 10

    h-index

1–5