Point Cloud Reconstruction

Point Cloud Reconstruction is a computational method in 3D reconstruction that generates a set of spatially distributed points representing the surface geometry of a physical object or scene from raw sensor data, distinguishing itself by directly producing unstructured point-wise representations without intermediate meshing or volumetric modeling.

1.5K

Publications

91.2K

Citations

4.5K

Authors

1.1K

Institutions

Publications per year

2017–2026

894

Authors

4.5K

  1. WG
    Wei Gao

    Peking University, China

    19 publications · 518 citations

    16

    h-index

  2. YL
    Yu-Shen Liu

    Tsinghua University, China

    18 publications · 1.4K citations

    16

    h-index

  3. FR
    Fabio Remondino

    Fondazione Bruno Kessler, Italy

    19 publications · 1.5K citations

    15

    h-index

  4. DC
    Daniel Cohen‐Or

    Tel Aviv University, Israel

    17 publications · 2.8K citations

    15

    h-index

  5. ZH
    Zhizhong Han

    Tsinghua University, China

    13 publications · 1.3K citations

    13

    h-index

1–5 of 4.5K

Venues

  1. arXiv (Cornell University)

    Repository · 60 publications · 2.1K citations

    27

    h-index

  2. ACM Transactions on Graphics

    TOG · 30 publications · 3.7K citations

    27

    h-index

  3. 27

    h-index

  4. Remote Sensing

    47 publications · 2.9K citations

    25

    h-index

  5. Sensors

    44 publications · 1.5K citations

    25

    h-index

1–5