Frequency‐Aware Spatial‐Angular Gaussians for Efficient Global Illumination Precomputation and Real‐Time Rendering

Abstract Precomputation and efficient approximate material models are well‐known approaches for achieving real‐time rendering with global illumination. Recent research in radiance fields and in particular 3D Gaussian Splatting has demonstrated the power of Gaussian primitives both to represent radiance and for fast optimization. Inspired by these advances, we propose a new representation to precompute global illumination, by using 3D Gaussians for the spatial and spherical Gaussians for the directional component of lighting. Critically, we precompute and store incoming radiance, thus requiring the optimization of a spatially smooth function, and we exploit the properties of anisotropic spherical Gaussians for very fast evaluation during rendering. We introduce a frequency‐aware sampling method, that guides both the placement of precomputed ground truth illumination samples and the placement of the Gaussians, both spatial and angular. Our approach provides very fast optimization, for a total precomputation time of less than 6 minutes for our test scenes, and better quality rendering than competing approaches at the same frame rates.