NeurIPS2024
Codec Avatar Studio: Paired Human Captures for Complete, Driveable, and Generalizable Avatars
Julieta Martinez, Emily Kim, Javier Romero, Timur M. Bagautdinov, Shunsuke Saito, Shoou-I Yu, Stuart Anderson, Michael Zollhöfer, Te-Li Wang, Shaojie Bai, Chenghui Li, Shih-En Wei, Rohan Joshi, Wyatt Borsos, Tomas Simon, Jason M. Saragih, Paul Theodosis, Alexander Greene, Anjani Josyula, Silvio Maeta, Andrew Jewett, Simion Venshtain, Christopher Heilman, Yueh-Tung Chen, Sidi Fu, Mohamed Elshaer, Tingfang Du, Longhua Wu, Shen-Chi Chen, Kai Kang, Michael Wu, Youssef Emad, Steven Longay, Ashley Brewer, Hitesh Shah, James Booth, Taylor Koska, Kayla Haidle, Matthew Andromalos, Joanna Hsu, Thomas Dauer, Peter Selednik, Timothy Godisart, Scott Ardisson, Matthew Cipperly, Ben Humberston, Lon Farr, Bob Hansen, Peihong Guo, Dave Braun, Steven Krenn, He Wen, Lucas Evans, Natalia Fadeeva, Matthew Stewart, Gabriel Schwartz, Divam Gupta, Gyeongsik Moon, Kaiwen Guo, Yuan Dong, Yichen Xu, Takaaki Shiratori, Fabian Prada, Bernardo Pires, Bo Peng, Julia Buffalini, Autumn Trimble, Kevyn McPhail, Melissa Schoeller, Yaser Sheikh
Abstract
To create photorealistic avatars that users can embody, human modeling must be complete (encompass the full body), driveable (able to reproduce motion of the user from lightweight sensors)