Depth Cue Integration

Depth Cue Integration is a computational process in visual perception research that combines multiple sources of depth information, such as binocular disparity, motion parallax, and pictorial cues, to form a unified and coherent estimate of three-dimensional scene structure.

114

Publications

7.5K

Citations

291

Authors

159

Institutions

Publications per year

2017–2026

19

Authors

291

  1. AE
    Andrew E. Welchman

    University of Birmingham, United Kingdom

    7 publications · 504 citations

    7

    h-index

  2. HB
    Hiroshi Ban

    The University of Osaka, Japan

    6 publications · 314 citations

    6

    h-index

  3. FD
    Fulvio Domini

    Brown University, United States

    6 publications · 112 citations

    6

    h-index

  4. CC
    Corrado Caudek

    University of Florence, Italy

    5 publications · 101 citations

    5

    h-index

  5. MS
    Michael S. Landy

    New York University, United States

    5 publications · 943 citations

    5

    h-index

1–5 of 291

Venues

  1. Vision Research

    17 publications · 1.3K citations

    14

    h-index

  2. Journal of Vision

    11 publications · 1.2K citations

    11

    h-index

  3. Perception

    5 publications · 261 citations

    5

    h-index

  4. 5

    h-index

  5. Nature Neuroscience

    4 publications · 532 citations

    4

    h-index

1–5