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Learning multi-grained interpretable latent representation for 3D face manipulation

Wenjing Gao Naye Ji Xi Li Dingguo Yu

计算可视媒体（英文）2025，Vol.11Issue(6)：1227-1246,20.

计算可视媒体（英文）2025，Vol.11Issue(6)：1227-1246,20.DOI:10.26599/CVM.2025.9450463

Learning multi-grained interpretable latent representation for 3D face manipulation

Wenjing Gao ¹Naye Ji ²Xi Li ¹Dingguo Yu²

作者信息

1. College of Computer Science & Technology,Zhejiang University,Hangzhou 310013,China
2. College of Media Engineering,Communication University of Zhejiang,Hangzhou 310018,China||Key Lab of Film and TV Media Technology of Zhejiang Province,Communication University of Zhejiang,Hangzhou 310018,China
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摘要

关键词

generative models/3D faces/multi-level interpretability/hierarchical semantic regu-larization

Key words

generative models/3D faces/multi-level interpretability/hierarchical semantic regu-larization

引用本文复制引用

Wenjing Gao,Naye Ji,Xi Li,Dingguo Yu..Learning multi-grained interpretable latent representation for 3D face manipulation[J].计算可视媒体（英文）,2025,11(6):1227-1246,20.

基金项目

This work was supported by the National Natural Science Foundation of China(62206241 and 62002316). （62206241 and 62002316）

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