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DTSTAMP:20260417T190157Z
LOCATION:West Building\, Rooms 220-222
DTSTART;TZID=America/Los_Angeles:20250812T112500
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UID:siggraph_SIGGRAPH 2025_sess150_papers_410@linklings.com
SUMMARY:Semantically Consistent Text-to-Motion with Unsupervised Styles
DESCRIPTION:Linjun Wu and Xiangjun Tang (Zhejiang University; State Key La
 boratory of CAD&CG, Zhejiang University); Jingyuan Cong (University of Cal
 ifornia San Diego); He Wang (UCL Centre for Artificial Intelligence, Depar
 tment of Computer Science, University College London (UCL)); Bo Hu, Xu Gon
 g, Songnan Li, and Yuchen Liao (Tencent Technology (Shenzhen) Co., Ltd.); 
 Yiqian Wu (Zhejiang University); Chen Liu (State Key Lab of CAD and CG, Zh
 ejiang University); and Xiaogang Jin (Zhejiang University; State Key Labor
 atory of CAD&CG, Zhejiang University)\n\nWe introduce a novel method that 
 integrates unsupervised style from arbitrary references into a text-driven
  diffusion model to generate semantically consistent stylized human motion
 . We leverage text as a mediator to capture the temporal correspondences b
 etween motion and style, enabling the seamless integration of temporally d
 ynamic style into motion features.\n\nInterest Area: Research & Education\
 n\nRecording: Livestreamed, Not Livestreamed, Recorded, Not Recorded\n\nRe
 gistration Category: Full Conference, Virtual Access, Tuesday\n\nSession C
 hair: Sheldon Andrews (École de Technologie Supérieure (ÉTS), McGill Unive
 rsity)\n\n
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