Unbiased and consistent rendering using biased estimators

Zackary Misso, Benedikt Bitterli, Iliyan Georgiev, Wojciech Jarosz

SIGGRAPH 2022 (journal)

Decomposition of our unbiased photon mapping into the sum of a biased estimate and a bias term. We separate the bias into positive and negative parts for ease of visualization.

Abstract

We introduce a general framework for transforming biased estimators into unbiased and consistent estimators for the same quantity. We show how several existing unbiased and consistent estimation strategies in rendering are special cases of this framework, and are part of a broader debiasing principle. We provide a recipe for constructing estimators using our generalized framework and demonstrate its applicability by developing novel unbiased forms of transmittance estimation, photon mapping, and finite differences.

Downloads and links

paper (PDF, 17 MB)
slides – from the conference presentation (KEY, 40 MB)
fast-forward video (MP4, 1.3 MB)
talk video (MP4, 21 MB)
code – reference implementation
citation (BIB)

Media

Fast-forward video

Talk video

BibTeX reference

@article{Misso:2022:Debiasing,
  author = {Zackary Misso and Benedikt Bitterli and Iliyan Georgiev and Wojciech Jarosz},
  title = {Unbiased and consistent rendering using biased estimators},
  journal = {ACM Transactions on Graphics (Proceedings of SIGGRAPH)},
  year = {2022},
  volume = {41},
  number = {4},
  doi = {10.1145/3528223.3530160}
}