EARS: Efficiency-Aware Russian Roulette and Splitting (SIGGRAPH 2022)
Channel: Alexander Rath
Date: 2022-06-28

This is the SIGGRAPH 2022 presentation video for our paper "EARS: Efficiency-Aware Russian Roulette and Splitting". I had a cold while recording this, so sorry for the coarse voice :-) Visit https://graphics.cg.uni-saarland.de/publications/rath-sig2022.html for more information!

Russian roulette and splitting are widely used techniques to increase the efficiency of Monte Carlo estimators. But, despite their popularity, there is little work on how to best apply them. Most existing approaches rely on simple heuristics based on, e.g., surface albedo and roughness. Their efficiency often hinges on user-controlled parameters. We instead iteratively learn optimal Russian roulette and splitting factors during rendering, using a simple and lightweight data structure. Given perfect estimates of variance and cost, our fixed-point iteration provably converges to the optimal Russian roulette and splitting factors that maximize the rendering efficiency. In our application to unidirectional path tracing, we achieve consistent and significant speed-ups over the state of the art.

00:47 Background
04:57 Previous Work
08:14 Our Approach
10:58 Results