WORLD-SPACE SPATIOTEMPORAL RESERVOIR REUSE FOR RAY-TRACED GLOBAL ILLUMINATION

Abstract

Path-traced global illumination of scenes with complex lighting remains particularly challenging at real-time framerates. Reservoir-based resampling methods for light sampling allow for significant noise reduction at the cost of very few shadow rays per pixel. However, current image-space approaches to reservoir reuse do not scale to sample lighting at further bounces, as is required for efficiently evaluating indirect illumination. We present a novel approach to performing reservoir-based spatiotemporal importance resampling in world space, allowing for efficient light sampling at arbitrary vertices along the eye path. Our approach caches the reservoirs of the path vertices into the cells of a hash grid built entirely on the GPU. Such a structure allows for stochastic reuse of neighboring reservoirs across space and time for efficient spatiotemporal reservoir resampling at any point in space.