Multiple Importance Sampling (MIS) is a key technique for achieving robustness of Monte
Carlo estimators in computer graphics and other fields. We derive optimal weighting …

We study Markov Chain Monte Carlo (MCMC) methods operating in primary sample space
and their interactions with multiple sampling techniques. We observe that incorporating the …

Finding good global importance sampling strategies for Monte Carlo light transport is
challenging. While estimators using local methods (such as BSDF sampling or next event …

Sony Imageworks' implementation of the Arnold renderer is a fork of the commercial product
of the same name, which has evolved independently since around 2009. This article focuses …

The development of general-purpose and efficient global illumination algorithms is one of
the foundational problems in computer graphics. Physics-based Monte Carlo rendering …

Two decades have passed since the introduction of Markov chain Monte Carlo (MCMC) into
light transport simulation by Veach and Guibas, and numerous follow-up works have been …

Complex visual effects such as caustics are often produced by light paths containing
multiple consecutive specular vertices (dubbed specular chains), which pose a challenge to …

Many existing Monte Carlo methods rely on multiple importance sampling (MIS) to achieve
robustness and versatility. Typically, the balance or power heuristics are used, mostly thanks …

Path guiding is a promising tool to improve the performance of path tracing algorithms.
However, not much research has investigated what target densities a guiding method …

The modern realistic computer graphics is based on physically correct lighting simulation.
One of the main and computationally difficult problems is the calculation of light transport or …