Presentation

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Importance Sampling BRDF Derivatives
SessionDifferentiable Rendering
DescriptionWe propose the first set of techniques to efficiently importance sample the derivatives of several popular analytical BRDF models (e.g. anisotropic GGX/ Beckmann/ Ashikhmin-Shirley, Hanrahan-Kreuger, Oren-Nayar etc.). Our estimators are practical and provide significant variance improvement in all settings from direct illumination to global illumination effects like caustics.
Authors
Yash Belhe
University of California San Diego
Bing Xu
University of California San Diego
Sai Praveen Bangaru
Massachusetts Institute of Technology (MIT)
Ravi Ramamoorthi
University of California San Diego
Tzu-Mao Li
University of California San Diego
Presenter
Yash Belhe
University of California San Diego
Event Type
Technical Paper
TimeMonday, 29 July 20242:10pm - 2:20pm MDT
LocationMile High 4
ACM Digital Library Journal Papers' PDFs
Conference Papers' PDFs
Session Time & Location
Sunday, 28 July 20246:00pm - 8:45pm MDTBluebird Ballroom
Monday, 29 July 20242:00pm - 3:30pm MDTMile High 4
Interest Areas
Research & Education
Recordings
Livestreamed
Recorded
Keywords
Machine Learning
Rendering
Registration Categories
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