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DTSTAMP:20250522T212947Z
LOCATION:Mile High 4
DTSTART;TZID=America/Denver:20240731T104500
DTEND;TZID=America/Denver:20240731T105500
UID:siggraph_SIGGRAPH 2024_sess129_papers_415@linklings.com
SUMMARY:LGTM: Local-to-Global Text-driven Human Motion Diffusion Model
DESCRIPTION:Haowen Sun and Ruikun Zheng (Shenzhen University), Haibin Huan
 g (Kuaishou Technology), Chongyang Ma (ByteDance Inc.), and Hui Huang and 
 Ruizhen Hu (Shenzhen University)\n\nWe introduce LGTM, a novel Local-to-Gl
 obal pipeline for Text-to-Motion generation based on diffusion model. It  
 decomposes motion description to body-part level with LLMs and encodes the
 m with corresponding body part motion individually, then optimizes whole b
 ody motion by attention encoder. As a result, it can generate local semant
 ics well-matched motion.\n\nInterest Area: Research & Education\n\nRecordi
 ng: Livestreamed, Recorded\n\nKeyword: Animation\n\nRegistration Category:
  Full Conference, Full Conference Supporter, Virtual Access, Exhibitor Ful
 l Conference, Wednesday\n\nSession Chair: Libin Liu (Peking University)\n\
 n
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