VarGes:Improving variation in co-speech 3D gesture generation via StyleCLIPSOA
VarGes:Improving variation in co-speech 3D gesture generation via StyleCLIPS
Ming Meng;Ke Mu;Yonggui Zhu;Zhe Zhu;Haoyu Sun;Heyang Yan;Zhaoxin Fan
School of Data Science and Media Intelligence,Communication University of China,Beijing 100024,ChinaSchool of Data Science and Media Intelligence,Communication University of China,Beijing 100024,ChinaSchool of Data Science and Media Intelligence,Communication University of China,Beijing 100024,ChinaSamsung Research America,Sun Jose 95134,CA,USAHainan International College,Communication University of China,Hainan 572423,ChinaSchool of Data Science and Media Intelligence,Communication University of China,Beijing 100024,ChinaBeijing Advanced Innovation Center for Future Blockchain and Privacy Computing,Institute of Artificial Intelligence,Beihang University,Beijing 100191,China||Hangzhou International Innovation Institute,Beihang University,Hangzhou 310051,China
gesture generationvariation enhancementmulti-modal fusionautoregressive modeling
gesture generationvariation enhancementmulti-modal fusionautoregressive modeling
《计算可视媒体（英文）》 2025 (6)
1263-1279,17
This work was supported by the Beijing Natural Science Foundation(No.4254100),the National Natural Science Foundation of China(Nos.11571325,62441617),the State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(No.VRLAB2023C04),the Fundamental Research Funds for the Central Universities(Nos.CUC2019A002,KG16336301)and Pubic Computing Cloud,CUC,and the China Postdoctoral Science Foundation(No.2024M764093).
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