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DTSTAMP:20240214T070248Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T090000
DTEND;TZID=Australia/Melbourne:20231215T091500
UID:siggraphasia_SIGGRAPH Asia 2023_sess155_papers_439@linklings.com
SUMMARY:Manifold Path Guiding for Importance Sampling Specular Chains
DESCRIPTION:Technical Papers\n\nZhimin Fan (Nanjing University); Pengpei H
 ong (University of Utah); Jie Guo (Nanjing University); Changqing Zou (Zhe
 jiang Lab; State Key Lab of CAD&CG, Zhejiang University); Yanwen Guo (Nanj
 ing University); and Ling-Qi Yan (University of California, Santa Barbara)
 \n\nComplex visual effects such as caustics are often produced by light pa
 ths containing multiple consecutive specular vertices (dubbed specular cha
 ins), which pose a challenge to unbiased estimation in Monte Carlo renderi
 ng.\nIn this work, we study the light transport behavior within a sub-path
  that is comprised of a specular chain and two non-specular separators. \n
 We show that the specular manifolds formed by all the sub-paths could be e
 xploited to provide coherence among sub-paths. By reconstructing continuou
 s energy distributions from historical and coherent sub-paths, seed chains
  can be generated in the context of importance sampling and converge to ad
 missible chains through manifold walks. We verify that importance sampling
  the seed chain in the continuous space reaches the goal of importance sam
 pling the discrete admissible specular chain. \nBased on these observation
 s and theoretical analyses, a progressive pipeline, manifold path guiding,
  is designed and implemented to importance sample challenging paths featur
 ing long specular chains. To our best knowledge, this is the first general
  framework for importance sampling discrete specular chains in regular Mon
 te Carlo rendering. Extensive experiments demonstrate that our method outp
 erforms state-of-the-art unbiased solutions with up to 40× variance reduct
 ion, especially in typical scenes containing long specular chains and comp
 lex visibility.\n\nRegistration Category: Full Access\n\nSession Chair: Si
 ng Chun Lee (Bucknell University)
URL:https://asia.siggraph.org/2023/full-program?id=papers_439&sess=sess155
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