“End-to-end Automatic Body and Face Setup for Generative or User Created 3D Avatar” by Shi, Chu, Kneubuehler, Teng, Burr, et al. …
Conference:
Type(s):
Title:
- End-to-end Automatic Body and Face Setup for Generative or User Created 3D Avatar
Session/Category Title: Bodies, Skin, and Hair
Presenter(s)/Author(s):
Abstract:
We propose and implement a production level end-to-end pipeline to automatically bridge the gap between 3D humanoid models and body and facial animation ready avatars that are highly customizable with different clothing and accessories. Our pipeline can support a large variety of input, from realistic humans, robots, aliens to monsters.
References:
[1]
Binh Le and Zhigang Deng. 2012. Smooth Skinning Decomposition with Rigid Bones. ACM Trans. Graph. 31, 6 (Dec. 2012). in press.
[2]
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas. 2017. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in neural information processing systems 30 (2017).
[3]
Nicholas Sharp, Souhaib Attaiki, Keenan Crane, and Maks Ovsjanikov. 2022. Diffusionnet: Discretization agnostic learning on surfaces. ACM Transactions on Graphics (TOG) 41, 3 (2022), 1–16.
[4]
Olga Sorkine and Marc Alexa. 2007. As-rigid-as-possible surface modeling. In Symposium on Geometry processing, Vol. 4. Citeseer, 109–116.
[5]
Zhan Xu, Yang Zhou, Evangelos Kalogerakis, Chris Landreth, and Karan Singh. 2020. RigNet: Neural Rigging for Articulated Characters. ACM Trans. on Graphics 39 (2020).
