Data-driven Reflectance Models
Data-Driven Reflectance Models is a reflectance modeling approach that belongs to the class of computational methods for estimating surface appearance from measured data, distinguished by its reliance on empirical observations and statistical learning rather than analytical physical simulations to characterize light-surface interactions.
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5.3K
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155
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98
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2017–2026
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A data-driven reflectance model
Wojciech Matusik, Hanspeter Pfister, Matt Brand et al. · ACM Transactions on Graphics · 2003 · 614 citations
A data-driven reflectance model
Wojciech Matusik, Hanspeter Pfister, Matt Brand et al. · 2003 · 603 citations · Full text
Zhe Zhu, Curtis E. Woodcock, Christopher E. Holden et al. · Remote Sensing of Environment · 2015 · 314 citations · Full text
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Tsinghua University
Beijing, China
3 h-index
5 publications
255 citations

University of Toronto
Toronto, Canada
3 h-index
6 publications
313 citations
State Key Laboratory of Remote Sensing Science
Beijing, China
3 h-index
17 publications
1.1K citations
University College London
London, United Kingdom
3 h-index
6 publications
1.1K citations
ETH Zurich
Zurich, Switzerland
3 h-index
5 publications
761 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
3 h-index
3 publications
207 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
13 publications
290 citations

Beijing Normal University
Beijing, China
3 h-index
13 publications
266 citations
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TOG · 7 publications · 1.3K citations
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6 publications · 1.1K citations
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2 publications · 41 citations
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TPAMI · 2 publications · 229 citations
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GR · 1 publications · 53 citations
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