Stochastic Image Generation

Stochastic Image Generation is a procedural image generation method that employs probabilistic models to produce visual outputs, distinguishing itself through the incorporation of randomness and statistical variation in the synthesis process.

48

Publications

5.9K

Citations

138

Authors

79

Institutions

Publications per year

2017–2026

14

Authors

138

  1. LR
    Lingmin Ran

    National University of Singapore, Singapore

    2 publications · 92 citations

    2

    h-index

  2. JS
    Jonathan Shade

    Microsoft Research (United Kingdom), United Kingdom

    2 publications · 595 citations

    2

    h-index

  3. MF
    Michael F. Cohen

    Microsoft (United States), United States

    2 publications · 595 citations

    2

    h-index

  4. DF
    Don Fussell

    The University of Texas at Austin, United States

    2 publications · 839 citations

    2

    h-index

  5. AG
    André Gagalowicz

    Institut national de recherche en sciences et technologies du numérique, France

    2 publications · 131 citations

    2

    h-index

1–5 of 138

Venues

  1. Computer Graphics Forum

    3 publications · 144 citations

    3

    h-index

  2. ACM Transactions on Graphics

    TOG · 3 publications · 342 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 2 publications · 29 citations

    2

    h-index

  4. 2

    h-index

  5. Frontiers in Water

    1 publications · 24 citations

    1

    h-index

1–5