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DTSTAMP:20260114T163647Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T140000
DTEND;TZID=Australia/Melbourne:20231214T141000
UID:siggraphasia_SIGGRAPH Asia 2023_sess151_papers_759@linklings.com
SUMMARY:Neural Collision Fields for Triangle Primitives
DESCRIPTION:Ryan Zesch (Texas A&M University), Vismay Modi (University of 
 Toronto), Shinjiro Sueda (Texas A&M University), and David Levin (Universi
 ty of Toronto)\n\nWe present neural collision fields as an alternative to 
 contact point sampling in physics simulations.\nOur approach is built on t
 op of a novel smoothed integral formulation for the contact surface patche
 s between two triangle meshes. By reformulating collisions as an integral,
  we avoid issues of sampling common to many collision-handling algorithms.
  Because the resulting integral is difficult to evaluate numerically, we s
 tore its solution in an integrated neural collision field --- a 6D neural 
 field in the space of triangle pair vertex coordinates. Our network genera
 lizes well to new triangle meshes without retraining. We demonstrate the e
 ffectiveness of our method by implementing it as a constraint in a positio
 n-based dynamics framework and show that our neural formulation successful
 ly handles collisions in practical simulations involving both volumetric a
 nd thin-shell geometries.\n\nRegistration Category: Full Access\n\nSession
  Chair: Tao Du (Tsinghua University, Shanghai Qi Zhi Institute)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_759&sess=sess151
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