Authentic Volumetric Avatars From a Phone Scan (SIGGRAPH 2022)

Paper: Authors: Chen Cao, Tomas Simon, Jin Kyu Kim, Gabe Schwartz, Michael Zollhoefer, Shunsuke Saito, Stephen Lombardi, Shih-en Wei, Danielle Belko, Shoou-i Yu, Yaser Sheikh, Jason Saragih Abstract: Creating photorealistic avatars of existing people currently requires extensive person-specific data capture, a process that has been primarily employed in the VFX industry due to its complexity. Our work aims to address this drawback by relying only on a short mobile phone capture to obtain a drivable 3D head avatar that matches a person’s likeness faithfully. In contrast to existing approaches, our architecture avoids the complex task of directly modeling the entire manifold of human appearance, aiming instead to generate an avatar model that can be specialized to novel identities using only small amounts of data. The model dispenses with low-dimensional latent spaces that are commonly employed for hallucinating nov