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
49
Zeliang Liu, Cheng Wu, M. Koishi · Computer Methods in Applied Mechanics and Engineering · 2018 · 304 citations · Full text
Natural Sciences, Materials Engineering, Materials Science +17
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103
Adobe Systems (United States)
San Jose, United States
6 h-index
18 publications
567 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
10 publications
951 citations

University of Toronto
Toronto, Canada
2 h-index
2 publications
32 citations
University of California System
Oakland, United States
2 h-index
4 publications
142 citations
Lutheran School of Theology at Chicago
Chicago, United States
2 h-index
4 publications
990 citations
University of California San Diego
San Diego, United States
2 h-index
6 publications
123 citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
2 h-index
2 publications
121 citations

Imperial College London
London, United Kingdom
2 h-index
2 publications
121 citations
1–8 of 103
TOG · 4 publications · 167 citations
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4 publications · 884 citations
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3 publications · 154 citations
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2 publications · 50 citations
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2 publications · 362 citations
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