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DTSTAMP:20260114T163657Z
LOCATION:Meeting Room C4.3\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T130000
DTEND;TZID=Australia/Melbourne:20231215T133000
UID:siggraphasia_SIGGRAPH Asia 2023_sess211_doc_118@linklings.com
SUMMARY:Modeling Dynamic Clothing for Data-Driven Photorealistic Avatars
DESCRIPTION:Donglai Xiang (Carnegie Mellon University)\n\nThis thesis pres
 ents research on building photorealistic avatars of humans wearing complex
  clothing in a data-driven manner. First, we introduce a separate two-laye
 r representation that allows us to disentangle the dynamics between the po
 se-driven body part and temporally-dependent clothing part. Second, we fur
 ther combine physics-based cloth simulation with a physics-inspired neural
  rendering model to generate rich and natural dynamics and appearance even
  for challenging clothing such as a skirt and a dress. Last, we go beyond 
 pose-driven animation and incorporate online sensor input into the avatars
  to achieve more faithful telepresence of clothing.\n\nRegistration Catego
 ry: Full Access\n\nSession Chair: Aaron Quigley (CSIRO's Data61)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=doc_118&sess=sess211
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