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SwitchLight: Co-design of Physics-driven Architecture and Pre-training Framework for Human Portrait Relighting
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We introduce a co-designed approach for human portrait relighting that combines a physics-guided architecture with a pre-training framework. Drawing on the Cook-Torrance reflectance model, we have meticulously configured the architecture design to precisely simulate light-surface interactions. Furthermore, to overcome the limitation of scarce high-quality lightstage data, we have developed a self-supervised pre-training strategy. This novel combination of accurate physical modeling and expanded training dataset establishes a new benchmark in relighting realism.
Forward citations
Cited by 2 Pith papers
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Relightable Full-Body Gaussian Codec Avatars
A full-body 3D avatar model that combines learned zonal-harmonic light transport, a shadow network, and deferred shading for relighting and animation of body, face, and hands.
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Text2Relight: Creative Portrait Relighting with Text Guidance
Text2Relight learns to re-light portrait photos from text prompts using a synthetic dataset generated by a three-stage pipeline.
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