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DTSTAMP:20250522T212945Z
LOCATION:Mile High 4
DTSTART;TZID=America/Denver:20240731T142000
DTEND;TZID=America/Denver:20240731T143000
UID:siggraph_SIGGRAPH 2024_sess120_papers_258@linklings.com
SUMMARY:ContourCraft: Learning to Resolve Intersections in Neural Multi-ga
 rment Simulations
DESCRIPTION:Artur Grigorev (ETH Zürich, Max Planck Institue for Intelligen
 t Systems); Giorgio Becherini and Michael Black (Max Planck Institue for I
 ntelligent Systems); and Otmar Hilliges and Bernhard Thomaszewski (ETH Zür
 ich)\n\nWe present a learning-based solution for handling collisions and s
 elf-intersections. Our method robustly recovers from intersections introdu
 ced through missed collisions, self-penetrating bodies, or manually design
 ed multi-layer outfits. The technical core of our method is a novel inters
 ection contour loss that penalizes inter-penetrations and encourages rapid
  resolution thereof.\n\nInterest Area: Research & Education\n\nRecording: 
 Livestreamed, Recorded\n\nKeyword: Animation\n\nRegistration Category: Ful
 l Conference, Full Conference Supporter, Virtual Access, Exhibitor Full Co
 nference, Wednesday\n\nSession Chair: Yin Yang (University of Utah)\n\n
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