Point Cloud Surface Reconstruction

Point Cloud Surface Reconstruction is a computational method that, given a discrete set of three-dimensional points sampled from a physical surface, uniquely constructs a continuous geometric representation by determining the topological and geometric structure that best approximates the original manifold from which the points were drawn.

309

Publications

24.4K

Citations

926

Authors

360

Institutions

Publications per year

2017–2026

113

Authors

926

  1. DC
    Daniel Cohen‐Or

    Tel Aviv University, Israel

    8 publications · 760 citations

    8

    h-index

  2. HZ
    Hao Zhang

    Simon Fraser University, Canada

    7 publications · 957 citations

    7

    h-index

  3. YL
    Yu-Shen Liu

    Tsinghua University, China

    5 publications · 188 citations

    5

    h-index

  4. AT
    Andrea Tagliasacchi

    Google (United States), United States

    4 publications · 1.1K citations

    4

    h-index

  5. HS
    Hans‐Peter Seidel

    Max Planck Institute for Informatics, Germany

    4 publications · 175 citations

    4

    h-index

1–5 of 926

Venues

  1. Computer Graphics Forum

    16 publications · 1.9K citations

    14

    h-index

  2. Computers & Graphics

    13 publications · 345 citations

    12

    h-index

  3. ACM Transactions on Graphics

    TOG · 11 publications · 1.3K citations

    11

    h-index

  4. Computer-Aided Design

    11 publications · 571 citations

    11

    h-index

  5. 8

    h-index

1–5