Snapmoji: Instant Generation of Animatable Dual-Stylized Avatars
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866914376849555456 |
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| author | Chen, Eric M. Liu, Di Ma, Sizhuo Vasilkovsky, Michael Zhou, Bing Gao, Qiang Wang, Wenzhou Luo, Jiahao Metaxas, Dimitris N. Sitzmann, Vincent Wang, Jian |
| author_facet | Chen, Eric M. Liu, Di Ma, Sizhuo Vasilkovsky, Michael Zhou, Bing Gao, Qiang Wang, Wenzhou Luo, Jiahao Metaxas, Dimitris N. Sitzmann, Vincent Wang, Jian |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_11978 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Snapmoji: Instant Generation of Animatable Dual-Stylized Avatars Chen, Eric M. Liu, Di Ma, Sizhuo Vasilkovsky, Michael Zhou, Bing Gao, Qiang Wang, Wenzhou Luo, Jiahao Metaxas, Dimitris N. Sitzmann, Vincent Wang, Jian Graphics Computer Vision and Pattern Recognition 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. |
| title | Snapmoji: Instant Generation of Animatable Dual-Stylized Avatars |
| topic | Graphics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2503.11978 |