Abstract
Rendering translucent materials is costly: light transport algorithms need to simulate a large number of scattering events inside the material before reaching convergence. The cost is especially high for materials with a large albedo or a small mean-free-path, where higher-order scattering effects dominate. In simple terms, the paths get lost in the medium. Path guiding has been proposed for surface rendering to make convergence faster by guiding the sampling process. In this paper, we introduce a path guiding solution for translucent materials. We learn an adaptive approximate representation of the radiance distribution in the volume and use it to sample the scattering direction, combining it with phase function sampling by resampled importance sampling. The proposed method significantly improves the performance of light transport simulation in participating media, especially for small lights and media with refractive boundaries. Our method can handle any homogeneous participating medium, with high or low scattering, with high or low absorption, and from isotropic to highly anisotropic.
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We thank the reviewers for their valuable comments. This work was partially supported by the National
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Hong Deng is currently a master student of computer science at Nanjing University of Science and Technology. His main areas of interest are physically-based rendering, game development, and real-time graphics.
Beibei Wang is an associate professor at Nanjing University of Science and Technology. She received her Ph.D. degree from Shandong University in 2014 and visited Telecom ParisTech from 2012 to 2014. She worked as a postdoc in Inria from 2015 to 2017. She joined NJUST in March 2017. Her research interests include rendering
Rui Wang is a professor at the State Key Lab of CAD&CG, Zhejiang University. He is working in the area of computer graphics. His current interests are mainly in real-time rendering, realistic rendering, GPU-based computation, and 3D display techniques. He received his Ph.D. degree in mathematics in 2007 and bachelor degree in computer science from Zhejiang University in 2001. He was a visiting associate professor hosted by Prof. Kavita Bala at Cornell University in 2012-2014.
Nicolas Holzschuch is a senior researcher at INRIA Grenoble Rhone-Alpes, and the scientific leader of the MAVERICK research team. He received his Ph.D. degree from Grenoble University in 1996 and his habilitation in 2007. He joined INRIA in 1997. His research interests include photorealistic rendering and real-time rendering, with an emphasis on material models and participating media.
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Deng, H., Wang, B., Wang, R. et al. A practical path guiding method for participating media. Comp. Visual Media 6, 37–51 (2020). https://doi.org/10.1007/s41095-020-0160-1
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DOI: https://doi.org/10.1007/s41095-020-0160-1