Deep Surface Reconstruction

Deep Surface Reconstruction is a computational framework within the field of 3D geometry processing that leverages deep learning models to infer high-fidelity surface representations from sparse, noisy, or incomplete point cloud data by learning implicit or explicit geometric priors from large datasets.

64

Publications

3.9K

Citations

247

Authors

99

Institutions

Publications per year

2017–2026

58

Authors

247

  1. KJ
    Kui Jia

    South China University of Technology, China

    5 publications · 287 citations

    5

    h-index

  2. OS
    Olga Sorkine‐Hornung

    ETH Zurich, Switzerland

    3 publications · 392 citations

    3

    h-index

  3. SW
    Shihao Wu

    Tel Aviv University, Israel

    3 publications · 392 citations

    3

    h-index

  4. LQ
    Lin Qi

    Ocean University of China, China

    2 publications · 56 citations

    2

    h-index

  5. YW
    Yuxin Wen

    Dalian University of Technology, China

    2 publications · 120 citations

    2

    h-index

1–5 of 247

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 259 citations

    8

    h-index

  2. ACM Transactions on Graphics

    TOG · 4 publications · 358 citations

    4

    h-index

  3. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 2 publications · 91 citations

    2

    h-index

  4. International Journal of Computer Vision

    2 publications · 75 citations

    2

    h-index

  5. Advanced Functional Materials

    1 publications · 70 citations

    1

    h-index

1–5