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SwitchLight: Co-design of Physics-driven Architecture and Pre-training Framework for Human Portrait Relighting

About

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.

Hoon Kim, Minje Jang, Wonjun Yoon, Jisoo Lee, Donghyun Na, Sanghyun Woo• 2024

Related benchmarks

TaskDatasetResultRank
Diffuse albedo predictionFaceOLAT (test)
PSNR32.98
5
Video RelightingBodyReLux Captured Performers Dataset Held-out sequences and views 1.0 (test)
PSNR16.88
5
Diffuse albedo prediction3DRFE
PSNR31.08
5
Portrait RelightingPOLAR
LPIPS0.168
4
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