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DTSTAMP:20260817T171534Z
LOCATION:Hall B5 (2)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241206T091100
DTEND;TZID=Asia/Tokyo:20241206T092300
UID:siggraphasia_SIGGRAPH Asia 2024_sess140_papers_175@linklings.com
SUMMARY:Differentiable Owen Scrambling
DESCRIPTION:Bastien Doignies (Université Claude Bernard Lyon, LIRIS); Davi
 d Coeurjolly, Nicolas Bonneel, and Julie Digne (CNRS, LIRIS); and Jean-Cla
 ude Iehl and Victor Ostromoukhov (Université Claude Bernard Lyon, LIRIS)\n
 \nQuasi-Monte Carlo integration is at the core of rendering. This techniqu
 e estimates the value of an integral by evaluating the integrand at well-c
 hosen sample locations. These sample points are designed to cover the doma
 in as uniformly as possible to achieve better convergence rates than purel
 y random points. Deterministic low-discrepancy sequences have been shown t
 o outperform many competitors by guaranteeing good uniformity as measured 
 by the so-called discrepancy metric, and, indirectly, by an integer 𝑡 valu
 e relating the number of points falling into each domain stratum with the 
 stratum area (lower 𝑡 is better). To achieve randomness, scrambling techni
 ques produce multiple realizations preserving the 𝑡 value, making the cons
 truction stochastic. Among them, Owen scrambling is a popular approach tha
 t recursively permutes intervals for each dimension. However, relying on p
 ermutation trees makes it incompatible with smooth optimization frameworks
 . We present a differentiable Owen scrambling that regularizes permutation
 s. We show that it can effectively be used with automatic differentiation 
 tools for optimizing low-discrepancy sequences to improve metrics such as 
 optimal transport uniformity, integration error, designed power spectra or
  projective properties, while maintaining their initial 𝑡-value as guarant
 eed by Owen scrambling. In some rendering settings, we show that our optim
 ized sequences improve the rendering error.\n\nRegistration Category: Full
  Access, Full Access Supporter\n\nLanguage Format: English Language\n\nSes
 sion Chair: Seungyong Lee (POSTECH)\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_175&sess=sess140
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