High Quality Neural Relighting using Practical Zonal Illumination

dc.contributor.authorLin, Arvinen_US
dc.contributor.authorLin, Yimingen_US
dc.contributor.authorLi, Xiaohuien_US
dc.contributor.authorGhosh, Abhijeeten_US
dc.contributor.editorHaines, Ericen_US
dc.contributor.editorGarces, Elenaen_US
dc.date.accessioned2024-06-25T11:05:41Z
dc.date.available2024-06-25T11:05:41Z
dc.date.issued2024
dc.description.abstractWe present a method for high-quality image-based relighting using a practical limited zonal illumination field. Our setup can be implemented with commodity components with no dedicated hardware. We employ a set of desktop monitors to illuminate a subject from a near-hemispherical zone and record One-Light-At-A-Time (OLAT) images from multiple viewpoints. We further extrapolate sampling of incident illumination directions beyond the frontal coverage of the monitors by repeating OLAT captures with the subject rotation in relation to the capture setup. Finally, we train our proposed skip-assisted autoencoder and latent diffusion based generative method to learn a high-quality continuous representation of the reflectance function without requiring explicit alignment of the data captured from various viewpoints. This method enables smooth lighting animation for high-frequency reflectance functions and effectively manages to extend incident lighting beyond the practical capture setup's illumination zone. Compared to state-of-the-art methods, our approach achieves superior image-based relighting results, capturing finer skin pore details and extending to passive performance video relighting.en_US
dc.description.sectionheadersRelighting
dc.description.seriesinformationEurographics Symposium on Rendering
dc.identifier.doi10.2312/sr.20241150
dc.identifier.isbn978-3-03868-262-2
dc.identifier.issn1727-3463
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.2312/sr.20241150
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/sr20241150
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Reflectance modeling; Image-based rendering; Computational photography
dc.subjectCCS Concepts
dc.subjectComputing methodologies
dc.subject> Reflectance modeling
dc.subjectImage
dc.subjectbased rendering
dc.subjectComputational photography
dc.titleHigh Quality Neural Relighting using Practical Zonal Illuminationen_US
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