Neural Material Representation

Neural Material Representation is a computational framework within material representation that employs neural networks to learn and encode the appearance, microgeometry, and physical properties of materials from data, enabling data-driven synthesis and manipulation of material appearances in rendering.

49

Publications

4.1K

Citations

199

Authors

103

Institutions

Publications per year

2017–2026

32

Authors

199

  1. MH
    Miloš Hašan

    Adobe Systems (United States), United States

    5 publications · 142 citations

    5

    h-index

  2. RR
    Ravi Ramamoorthi

    University of California, Berkeley, United States

    4 publications · 112 citations

    4

    h-index

  3. ZX
    Zexiang Xu

    Adobe Systems (United States), United States

    3 publications · 95 citations

    3

    h-index

  4. ZL
    Zeliang Liu

    Northwestern University, United States

    3 publications · 553 citations

    3

    h-index

  5. FL
    Fujun Luan

    Adobe Systems (United States), United States

    3 publications · 128 citations

    3

    h-index

1–5 of 199

Venues

  1. ACM Transactions on Graphics

    TOG · 4 publications · 167 citations

    4

    h-index

  2. Psychophysiology

    4 publications · 884 citations

    4

    h-index

  3. Computer Graphics Forum

    3 publications · 154 citations

    3

    h-index

  4. Symmetry

    2 publications · 50 citations

    2

    h-index

  5. 2

    h-index

1–5