Lucas, SimonPacanowski, RomainBarla, PascalWang, BeibeiWilkie, Alexander2025-06-202025-06-2020251467-8659https://doi.org/10.1111/cgf.70174https://diglib.eg.org/handle/10.1111/cgf70174Importance sampling of visible normal distribution functions (vNDF) is a required ingredient for the efficient rendering of microfacet-based materials. In this paper, we explain how to sample the vNDF for the micrograin material model [LRPB23], which has been recently improved to handle height-normal correlations through a new Geometric Attenuation Factor (GAF) [LRPB24], leading to a stronger impact on appearance compared to the earlier Smith approximation. To this end, we make two contributions: we derive analytic expressions for the marginal and conditional cumulative distribution functions (CDFs) of the vNDF; we provide efficient methods for inverting these CDFs based respectively on a 2D lookup table and on the triangle-cut method [Hei20].Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Reflectance modelingComputing methodologies → Reflectance modeling10.1111/cgf.7017410 pages