Corentin Salaün

Corentin Salaün

PhD student at Max-Planck-Institut für Informatik

Scalable multi-class sampling via filtered sliced optimal transport

Corentin Salaün, Iliyan Georgiev, Hans-Peter Seidel, Gurprit Singh

ACM Siggraph asia 2022 (Journal track)
Published in ACM Transactions on Graphics, Volume 41, 2022

Teaser

Abstract

We propose a multi-class point optimization formulation based on continuous Wasserstein barycenters. Our formulation is designed to handle hundreds to thousands of optimization objectives and comes with a practical optimization scheme. We demonstrate the effectiveness of our framework on various sampling applications like stippling, object placement, and Monte-Carlo integration. We a derive multi-class error bound for perceptual rendering error which can be minimized using our optimization.

Presentation video

BibTeX reference

@article{Salaun:2022:ScalableMultiClassSampling,
    author = {Corentin Sala\"un and Iliyan Georgiev and Hans-Peter Seidel and Gurprit Singh},
    title = {Scalable multi-class sampling via filtered sliced optimal transport},
    journal = {ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia)},
    year = {2022},
    volume = {41},
    number = {6},
    doi = {10.1145/3550454.3555484}
}