CVPR2023
Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos
Ziqian Bai, Feitong Tan, Zeng Huang, Kripasindhu Sarkar, Danhang Tang, Di Qiu, Abhimitra Meka, Ruofei Du, Mingsong Dou, Sergio Orts-Escolano, Rohit Pandey, Ping Tan, Thabo Beeler, Sean Fanello, Yinda Zhang
Abstract
Figure 1 . Our technique builds a 3D avatar representation of a person using just a single short monocular RGB video (e.g., 1-2 minutes). We leverage a 3DMM to track the user's expressions. By anchoring a neural radiance field to the 3DMM geometry, we generate a volumetric photorealistic 3D avatar that can be rendered with user-defined expression and viewpoint. Note that our method works well on challenging materials, e.g., hair and dramatic expressions. Please see our webpage augmentedperception.github.io/monoavatar for more results.