Generative Image Composition

Generative Image Composition is a systematic framework within generative printmaking that orchestrates the autonomous arrangement and synthesis of visual elements through algorithmic or rule-based processes to produce novel, cohesive imagery distinct from manual or traditional composition methods.

23

Publications

2.1K

Citations

62

Authors

32

Institutions

Publications per year

2017–2026

17

Authors

62

  1. PT
    Ping Tan

    Simon Fraser University, Canada

    2 publications · 703 citations

    2

    h-index

  2. KM
    Kwan‐Liu Ma

    University of California, Davis, United States

    2 publications · 89 citations

    2

    h-index

  3. AS
    Ariel Shamir

    Reichman University, Israel

    2 publications · 703 citations

    2

    h-index

  4. MC
    Ming‐Ming Cheng

    Nankai University, China

    2 publications · 703 citations

    2

    h-index

  5. CD
    Carlos D. Correa

    University of California, Davis, United States

    2 publications · 89 citations

    2

    h-index

1–5 of 62

Venues

  1. ACM Transactions on Graphics

    TOG · 3 publications · 875 citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 42 citations

    3

    h-index

  3. 3

    h-index

  4. International Conference on Machine Learning

    Conference · 1 publications · 14 citations

    1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 39 citations

    1

    h-index

1–5