English

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

Computer Vision and Pattern Recognition 2024-03-01 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2402.18848,
  title  = {SwitchLight: Co-design of Physics-driven Architecture and Pre-training Framework for Human Portrait Relighting},
  author = {Hoon Kim and Minje Jang and Wonjun Yoon and Jisoo Lee and Donghyun Na and Sanghyun Woo},
  journal= {arXiv preprint arXiv:2402.18848},
  year   = {2024}
}

Comments

CVPR2024. Live demos available at https://www.beeble.ai/