Real-Time Path-Guiding Based on Parametric Mixture Models

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dc.contributor.authorDerevyannykh, Mikhailen_US
dc.contributor.editorPelechano, Nuriaen_US
dc.contributor.editorVanderhaeghe, Daviden_US
dc.date.accessioned2022-04-22T08:16:11Z
dc.date.available2022-04-22T08:16:11Z
dc.date.issued2022
dc.description.abstractPath-Guiding algorithms for sampling scattering directions can drastically decrease the variance of Monte Carlo estimators of Light Transport Equation, but their production usage was limited to offline rendering because of memory and computational limitations. We introduce a new robust screen-space technique that is based on online learning of parametric mixture models for guiding the real-time path-tracing algorithm. It requires storing of 8 parameters for every pixel, achieves a reduction of FLIP metric up to 4 times with 1 spp rendering. Also, it consumes less than 1.5ms on RTX 2070 for 1080p and reduces path-tracing timings by generating more coherent rays by about 5% on average. Moreover, it leads to significant bias reduction and a lower level of flickering of SVGF output.en_US
dc.description.sectionheadersRendering and Illumination
dc.description.seriesinformationEurographics 2022 - Short Papers
dc.identifier.doi10.2312/egs.20221024
dc.identifier.isbn978-3-03868-169-4
dc.identifier.issn1017-4656
dc.identifier.pages25-28
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/egs.20221024
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egs20221024
dc.publisherThe Eurographics Associationen_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
dc.subjectRay tracing
dc.titleReal-Time Path-Guiding Based on Parametric Mixture Modelsen_US
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