Name
Title | ||
|---|---|---|
Improving robustness of Monte-Carlo global illumination with directional regularization |
Abstract | ||
|---|---|---|
Directional regularization offers great potential to improve the convergence rates of Monte-Carlo-based global illumination algorithms. In this paper, we show how it can be applied successfully by combining unbiased bidirectional strategies, photon mapping, and biased directional regularization. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2542355.2542383 | SIGGRAPH Asia Technical Briefs |
Field | DocType | Citations |
Convergence (routing),Computer vision,Monte Carlo method,Computer science,Robustness (computer science),Regularization (mathematics),Global illumination,Artificial intelligence,Photon mapping,Variance reduction | Conference | 3 |
PageRank | References | Authors |
0.46 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guillaume Bouchard | 1 | 433 | 39.20 |
| Jean Claude Iehl | 2 | 3 | 0.46 |
| Victor Ostromoukhov | 3 | 717 | 61.60 |
| Pierre Poulin | 4 | 573 | 38.55 |