Neural Caching of Prefiltered Radiance for Specular Lighting

Dmitrii Klepikov; Vladimir Frolov

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arXiv · 2610.11702

Neural Caching of Prefiltered Radiance for Specular Lighting

Dmitrii Klepikov·Vladimir Frolov

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Abstract

Neural Radiance Caching (NRC) provides an online neural representation of scene illumination for real-time path tracing. This paper presents an NRC variant tailored to specular lighting through a reflection-direction parameterization and a roughness-dependent radiance target. Our network predicts prefiltered incoming radiance at individual surface points, which is combined with a precomputed BRDF integration map using the split-sum approximation to estimate outgoing radiance. On Bunny and Specular Sponza, the reported comparisons indicate faster convergence to the accumulated path-tracing reference and improved specular-lighting quality relative to the evaluated NRC baselines. Our online-trained method maintains real-time performance while adapting its cache during rendering.

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BibTeX RIS

Dmitrii Klepikov, Vladimir Frolov. 2026-10-08. Neural Caching of Prefiltered Radiance for Specular Lighting. https://arxiv.org/abs/2610.11702

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