Presentation
Toward Richer Material Generation via Procedural Data Enhancement
SessionLayouts & Procedural
DescriptionGenerative material models are limited by simple PBR data. We augment single-lobe GGX materials into layered, multi-lobe models capturing richer effects (e.g., dust, clearcoat). These are encoded as neural materials in a shared 6D latent space. The resulting dataset enables generative models to produce more expressive materials.
Event Type
Technical Paper
TimeTuesday, 21 July 20269:30am - 9:40am PDT
LocationRoom 403 A
Digital Library
PDF
Session Time & Location
Sunday, 19 July 20266:00pm - 8:45pm PDTHall K
Tuesday, 21 July 20269:00am - 10:30am PDTRoom 403 A
Artificial Intelligence/Machine Learning
Generative AI
Modeling
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