Computer Science > Computer Vision and Pattern Recognition
arXiv:2410.11625 (cs)
[Submitted on 15 Oct 2024]
Title:Fast Local Neural Regression for Low-Cost, Path Traced Lambertian Global Illumination
View a PDF of the paper titled Fast Local Neural Regression for Low-Cost, Path Traced Lambertian Global Illumination, by Arturo Salmi and 1 other authors
View PDFHTML (experimental)Abstract:Despite recent advances in hardware acceleration of ray tracing, real-time ray budgets remain stubbornly limited at a handful of samples per pixel (spp) on commodity hardware, placing the onus on denoising algorithms to achieve high visual quality for path traced global illumination. Neural network-based solutions give excellent result quality at the cost of increased execution time relative to hand-engineered methods, making them less suitable for deployment on resource-constrained systems. We therefore propose incorporating a neural network into a computationally-efficient local linear model-based denoiser, and demonstrate faithful single-frame reconstruction of global illumination for Lambertian scenes at very low sample counts (1spp) and for low computational cost. Other contributions include improving the quality and performance of local linear model-based denoising through a simplified mathematical treatment, and demonstration of the surprising usefulness of ambient occlusion as a guide channel. We also show how our technique is straightforwardly extensible to joint denoising and upsampling of path traced renders with reference to low-cost, rasterized guide channels.
| Comments: | 11 pages, 10 figures, 1 table |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR); Machine Learning (cs.LG) |
| ACM classes: | I.2; I.3; I.4 |
| Cite as: | arXiv:2410.11625 [cs.CV] |
| (orarXiv:2410.11625v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2410.11625 arXiv-issued DOI via DataCite |
Submission history
From: Szabolcs Cséfalvay [view email][v1] Tue, 15 Oct 2024 14:14:06 UTC (31,031 KB)
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View a PDF of the paper titled Fast Local Neural Regression for Low-Cost, Path Traced Lambertian Global Illumination, by Arturo Salmi and 1 other authors
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