A Data-Driven Approach to Analytical Dwivedi Guiding

dc.contributor.authorGouder, Darrylen_US
dc.contributor.authorVorba, Jiríen_US
dc.contributor.authorDroske, Marcen_US
dc.contributor.authorWilkie, Alexanderen_US
dc.contributor.editorWang, Beibeien_US
dc.contributor.editorWilkie, Alexanderen_US
dc.date.accessioned2025-06-20T07:53:12Z
dc.date.available2025-06-20T07:53:12Z
dc.date.issued2025
dc.description.abstractPath tracing remains the gold standard for high-fidelity subsurface scattering despite requiring numerous paths for noisefree estimates. We introduce a novel variance-reduction method based on two complementary zero-variance-theory-based approaches. The first one, analytical Dwivedi sampling, is lightweight but struggles with complex lighting. The second one, surface path guiding, learns incident illumination at boundaries to guide sampled paths, but it does not reduce variance from subsurface scattering. In our novel method, we enhance Dwivedi sampling by incorporating the radiance field learned only at the volume boundary. We use the average normal of points on an illuminated boundary region or directions sampled from distributions of incident light at the boundary as our analytical Dwivedi slab normals. Unlike previous methods based on Dwivedi sampling, our method is efficient even in scenes with complex light rigs typical for movie production and under indirect illumination. We achieve comparable noise reduction and even slightly improved estimates in some scenes compared to volume path guiding, and our method can be easily added on top of any existing surface path guiding system. Our method is particularly effective for homogeneous, isotropic media, bypassing the extensive training and caching inside the 3D volume that volume path guiding requires.en_US
dc.description.number4
dc.description.sectionheadersSampling and Guiding
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume44
dc.identifier.doi10.1111/cgf.70164
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.70164
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf70164
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Ray tracing
dc.subjectComputing methodologies → Ray tracing
dc.titleA Data-Driven Approach to Analytical Dwivedi Guidingen_US
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