Snapmoji: Instant Generation of Animatable Dual-Stylized Avatars

View at publisher
Authors: Eric Ming Chen, Di Liu, Sizhuo Ma, Michael Vasilkovsky, Bing Zhou, Qiang Gao, Wenzhou Wang, Jiahao Luo, Dimitris N. Metaxas, Vincent Sitzmann, Jian Wang
Cited by: 1
References: 38

Abstract

Despite the increasing popularity of avatar systems such as Snapchat Bitmojis, existing production avatar platforms face several limitations, such as a limited number of predefined assets, tedious customization processes, and inefficient rendering requirements. Addressing these shortcomings, we introduce Snapmoji, an avatar generation system that instantly creates 3D avatars, and enables customization in a process we call dual-stylization. Snapmoji first maps a selfie of a user to a primary avatar (e.g., Bitmoji style) using a new technique we name Gaussian Domain Adaptation (GDA), then applies a secondary style (e.g., skeleton, yarn, toy) to the primary avatar, all while preserving the user’s identity. The generated 3D avatars can then be rendered an animated on mobile devices at 30–40 FPS.

Fields of Study & Subjects

Human Motion and Animation Artificial Intelligence in Games Interactive and Immersive Displays

Publication details

Journal / source
2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Publisher
IEEE
Pages
1948–1958
Publication date
6 March 2026