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DTSTAMP:20250522T212946Z
LOCATION:Mile High 4
DTSTART;TZID=America/Denver:20240801T141000
DTEND;TZID=America/Denver:20240801T142000
UID:siggraph_SIGGRAPH 2024_sess143_papers_218@linklings.com
SUMMARY:Interactive Character Control With Auto-regressive Motion Diffusio
 n Models
DESCRIPTION:Yi Shi (Simon Fraser University, Shanghai Aritificial Intellig
 ence Laboratory); Jingbo Wang and Xuekun Jiang (Shanghai Aritificial Intel
 ligence Laboratory); Bingkun Lin (Xmov); Bo Dai (Shanghai Aritificial Inte
 lligence Laboratory); and Xue Bin Peng (Simon Fraser University, NVIDIA)\n
 \nWe present A-MDM, an auto-regressive diffusion model for kinematic motio
 n synthesis. A-MDM can be effectively trained with large motion datasets t
 o synthesize high-quality and diverse motions. Once trained, A-MDM can be 
 combined with various control methods to generate motions for new downstre
 am tasks.\n\nInterest Area: Research & Education\n\nRecording: Livestreame
 d, Recorded\n\nKeyword: Animation\n\nRegistration Category: Full Conferenc
 e, Full Conference Supporter, Virtual Access, Exhibitor Full Conference, T
 hursday\n\nSession Chair: Teseo Schneider (University of Victoria)\n\n
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