dc.contributor.author | Zhang, Xianyao | en_US |
dc.contributor.author | Röthlin, Gerhard | en_US |
dc.contributor.author | Manzi, Marco | en_US |
dc.contributor.author | Gross, Markus | en_US |
dc.contributor.author | Papas, Marios | en_US |
dc.contributor.editor | Ritschel, Tobias | en_US |
dc.contributor.editor | Weidlich, Andrea | en_US |
dc.date.accessioned | 2023-06-27T06:42:00Z | |
dc.date.available | 2023-06-27T06:42:00Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-228-8 | |
dc.identifier.issn | 1727-3463 | |
dc.identifier.uri | https://doi.org/10.2312/sr.20231142 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/sr20231142 | |
dc.description.abstract | Path tracing is the prevalent rendering algorithm in the animated movies and visual effects industry, thanks to its simplicity and ability to render physically plausible lighting effects. However, we must simulate millions of light paths before producing one final image, and error manifests as noise during rendering. In fact, it can take tens or even hundreds of CPU hours on a modern computer to render a plausible frame in a recent animated movie. Movie production and the VFX industry rely on image-based denoising algorithms to ameliorate the rendering cost, which suppresses the noise due to rendering by reusing information in the neighborhood of the pixels both spatially and temporally. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.title | Deep Compositional Denoising on Frame Sequences | en_US |
dc.description.seriesinformation | Eurographics Symposium on Rendering | |
dc.description.sectionheaders | Industry Track | |
dc.identifier.doi | 10.2312/sr.20231142 | |
dc.identifier.pages | 139-142 | |
dc.identifier.pages | 4 pages | |