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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:20260817T171532Z
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:Fu-Yun Wang (Chinese University of Hong Kong); Zhaoyang Huang 
 (Avolution AI); Weikang Bian, Xiaoyu Shi, and Keqiang Sun (Chinese Univers
 ity of Hong Kong); Guanglu Song (SenseTime); Yu Liu (Shanghai Artificial I
 ntelligence Laboratory); and Hongsheng Li (Chinese University of Hong Kong
 )\n\nComputation-efficient personalized style video generation without per
 sonalized video data, reducing generation time of similarly sized video di
 ffusion models from 25 seconds to around 1 second while maintaining compar
 able performance.\n\nRegistration Category: Full Access, Full Access Suppo
 rter\n\nLanguage Format: English Language\n\nSession Chair: Krishna Mullia
  (Canva Research)\n\n
URL:https://asia.siggraph.org/2024/program/?id=tcom_186&sess=sess288
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