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BEGIN:VEVENT
DTSTAMP:20260805T205604Z
LOCATION:Room 408 B
DTSTART;TZID=America/Los_Angeles:20260721T113500
DTEND;TZID=America/Los_Angeles:20260721T114500
UID:siggraph_SIGGRAPH 2026_sess144_paperstog_135@linklings.com
SUMMARY:Articulate That Object Part (ATOP): 3D Part Articulation from Text
  and via Motion Personalization
DESCRIPTION:Aditya Vora, Sauradip Nag, Kai Wang, and Hao (Richard) Zhang (
 Simon Fraser University) and Aditya Vora\n\nWe present a few-shot method f
 or articulating static 3D objects using text-guided motion personalization
 . Leveraging diffusion models, we generate plausible part motions and adap
 t them to input objects via image prompting. Differentiable rendering with
  score distillation transfers multi-view motion into 3D, enabling optimiza
 tion of articulation parameters under piecewise rigidity assumptions.\n\nI
 nterest Area: Research & Education\n\nKeyword: Artificial Intelligence/Mac
 hine Learning, Geometry, Modeling, Rendering, Virtual Reality\n\nRegistrat
 ion Category: Full Conference Supporter, Full Conference\n\nSession Chair:
  Yi Zhou (Roblox)\n\n
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