Illumination-Aware Spatial Subdivision for Path Guiding

Illumination-Aware Spatial Subdivision for Path Guiding

Fengshi Zheng, Christoph Peters, Sebastian Herholz, Marco Manzi, Elmar Eisemann.

2026–06 in Eurographics Symposium on Rendering. The Eurographics Association.

Official version

Abstract

Path tracing is ubiquitous in production rendering and path guiding has established itself as a powerful approach to mitigate its failure cases. Several widely used methods partition the scene using a k-d tree and store a directional guiding distribution per cell for importance sampling. While a lot of research has improved the guiding distributions, the decision when to split the k-d tree still relies on a simple sample count threshold. We propose a method to adapt the k-d tree depending on the variation in the illumination. To this end, we use lookahead cells, i.e.~multiple additional levels of k-d tree cells that do not store a guiding distribution. Instead, they store compact characterizations of the light field, which we call signatures. Specifically, we use the mean radiance and radiance-weighted mean direction. We model the uncertainty in these signatures probabilistically to derive split criteria that split k-d tree cells when we are confident that one of their lookahead cells differs substantially. As a result, we make existing guiding methods allocate computational and storage resources more efficiently, using small cells in regions with rapidly varying illumination whilst sharing data for uniformly lit regions.

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Notes

This work has been presented at EGSR 2026 on 1st of July.

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Paper

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TU Delft project webpage (additional materials)

Eurographics Digital Library