CVPR 2023 - NeuFace: Realistic 3D Neural Face Rendering from Multi-view Images

In this episode we discuss NeuFace: Realistic 3D Neural Face Rendering from Multi-view Images by Mingwu Zheng, Haiyu Zhang, Hongyu Yang, Di Huang. The paper presents a new 3D face rendering model, called Neu-Face, that uses neural rendering techniques to learn accurate and physically-meaningful underlying 3D representations. It incorporates the neural BRDFs (bidirectional reflectance distribution function) into physically based rendering to capture sophisticated facial geometry and appearance clues. The model uses approximated BRDF integration and a new low-rank prior to effectively lower ambiguities and boost performance. The experiments show the superiority of Neu-Face in human face rendering, with decent generalization ability to common objects. The code is available at NeuFace.