Speaker: Annalena Ulschmid
Abstract
Achieving realistic rendering of 3D scenes in real time using path tracing is challenging due to the high sample count required, with ray tracing as the bottleneck. Focusing on voxels as a geometry representation offers significant opportunities for optimizations, especially for tracing the rays, but also for computing the samples.
We propose a novel multilayered spatial structure augmented with in-cell axis-aligned distance fields (AADF) operating as caches.
Our nested cell structure already accelerates ray tracing 3-5x compared to the state-of-the-art dense spatial structures, such as variants of directed acyclic graphs (DAG). Using the AADFs (constructed while rendering) inside the cells, we can double the ray throughput again (total 10x). As an application, exploiting nested AADFs (NAADFs) also allows us to double the speed of global illumination computations while significantly reducing artifacts from camera motion, such as flickering, blurring, ghosting, and aliasing, all of which are especially important in voxel worlds with sharp edges. We achieve this by adapting temporal antialiasing (TAA) to retain the last 32 frames rather than a single history buffer to create the final antialiased image, since the discretized voxel structure requires much less memory to store the quantized positions and normals of ray bounces. The sample accumulation for global illumination is optimized by compressing and separating lit/unlit samples, and we apply 8x8 window spatial resampling based on a reservoir-based spatiotemporal importance resampling (ReSTIR) method. Our proposed NAADFs support editing with quick updates to the acceleration in the background, overlays of non-aligned dynamic geometry, and can be easily extended to support transform-aware compression or to represent huge real-world scans. Retaining many past frames rather than just combining them opens up new opportunities to remove spatial and temporal artifacts in path tracing for global illumination.