Multi-view Object Reconstruction

Multi-View Object Reconstruction is a computational method in computer vision that reconstructs three-dimensional object geometry by integrating visual information from multiple two-dimensional viewpoints, distinguished by its reliance on multi-view image correspondences and geometric consistency constraints.

98

Publications

4.7K

Citations

295

Authors

138

Institutions

Publications per year

2017–2026

21

Authors

295

  1. HS
    Heung‐Yeung Shum

    Microsoft Research Asia (China), China

    4 publications · 71 citations

    4

    h-index

  2. RR
    R. Reddy

    Carnegie Mellon University, United States

    3 publications · 59 citations

    3

    h-index

  3. TT
    T. Takai

    Kyoto University, Japan

    3 publications · 223 citations

    3

    h-index

  4. TM
    Takashi Matsuyama

    Kyoto University, Japan

    3 publications · 223 citations

    3

    h-index

  5. PK
    Peter K. Allen

    Columbia University, United States

    2 publications · 52 citations

    2

    h-index

1–5 of 295

Venues

  1. 8

    h-index

  2. International Journal of Computer Vision

    4 publications · 265 citations

    4

    h-index

  3. Computers & Electrical Engineering

    2 publications · 34 citations

    2

    h-index

  4. Applied Optics

    2 publications · 64 citations

    2

    h-index

  5. Computer Graphics Forum

    2 publications · 124 citations

    2

    h-index

1–5