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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:20260817T171520Z
LOCATION:Lobby Gallery (1) & (2)\, G Block\, Level B1
DTSTART;TZID=Asia/Tokyo:20241204T130000
DTEND;TZID=Asia/Tokyo:20241204T140000
UID:siggraphasia_SIGGRAPH Asia 2024_sess199_pos_171@linklings.com
SUMMARY:Generalizing Human Motion Style Transfer Method Based on Metadata-
 independent Learning
DESCRIPTION:Yuki Era, Ren Togo, Keisuke Maeda, Takahiro Ogawa, and Miki Ha
 seyama (Hokkaido University)\n\nThis study aims to extend the applicabilit
 y of motion style transfer methods to be robust for diverse and complex mo
 tions akin to those found in real-world data.\n\nRegistration Category: En
 hanced Access, Exhibit & Experience Access, Experience Hall Exhibitor, Ful
 l Access, Full Access Supporter, Trade Exhibitor\n\n
URL:https://asia.siggraph.org/2024/program/?id=pos_171&sess=sess195
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