BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Denver
X-LIC-LOCATION:America/Denver
BEGIN:DAYLIGHT
TZOFFSETFROM:-0700
TZOFFSETTO:-0600
TZNAME:MDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0600
TZOFFSETTO:-0700
TZNAME:MST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20250522T212945Z
LOCATION:Mile High 4
DTSTART;TZID=America/Denver:20240801T105500
DTEND;TZID=America/Denver:20240801T110500
UID:siggraph_SIGGRAPH 2024_sess146_papers_1111@linklings.com
SUMMARY:Text-guided Synthesis of Crowd Animation
DESCRIPTION:Xuebo Ji (University of Hong Kong, Centre for Transformative G
 arment Production (TransGP)); Zherong Pan and Xifeng Gao (Tencent America)
 ; and Jia Pan (University of Hong Kong, Centre for Transformative Garment 
 Production (TransGP))\n\nThis paper presents a novel approach to automatic
 ally generate crowd behaviors from high-level text descriptions. The group
 -wise, velocity-field-based representation of collective agent behaviors i
 s used and seamlessly integrated with diffusion models and large language 
 models. This work paves the way toward automatic crowd behavior generation
  for virtual environments.\n\nInterest Area: Research & Education\n\nRecor
 ding: Livestreamed, Recorded\n\nKeyword: Animation\n\nRegistration Categor
 y: Full Conference, Full Conference Supporter, Virtual Access, Exhibitor F
 ull Conference, Thursday\n\nSession Chair: Anton Kaplanyan (Intel)\n\n
END:VEVENT
END:VCALENDAR