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VERSION:2.0
PRODID:Linklings LLC
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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:JST
DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20250110T023303Z
LOCATION:G510\, G Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241205T132500
DTEND;TZID=Asia/Tokyo:20241205T133700
UID:siggraphasia_SIGGRAPH Asia 2024_sess288_tcom_186@linklings.com
SUMMARY:AnimateLCM: Computation-Efficient Personalized Style Video Generat
 ion without Personalized Video Data
DESCRIPTION:Technical Communications\n\nFu-Yun Wang (Chinese University of
  Hong Kong); Zhaoyang Huang (Avolution AI); Weikang Bian, Xiaoyu Shi, and 
 Keqiang Sun (Chinese University of Hong Kong); Guanglu Song (SenseTime); Y
 u Liu (Shanghai Artificial Intelligence Laboratory); and Hongsheng Li (Chi
 nese University of Hong Kong)\n\nComputation-efficient personalized style 
 video generation without personalized video data, reducing generation time
  of similarly sized video diffusion models from 25 seconds to around 1 sec
 ond while maintaining comparable performance.\n\nRegistration Category: Fu
 ll Access, Full Access Supporter\n\nLanguage Format: English Language\n\nS
 ession Chair: Krishna Mullia (Adobe Research)
URL:https://asia.siggraph.org/2024/program/?id=tcom_186&sess=sess288
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