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DTSTAMP:20260114T163655Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T141000
DTEND;TZID=Australia/Melbourne:20231214T142000
UID:siggraphasia_SIGGRAPH Asia 2023_sess151_papers_785@linklings.com
SUMMARY:Learning Contact Deformations with General Collider Descriptors
DESCRIPTION:Cristian Romero and Dan Casas (Universidad Rey Juan Carlos) an
 d Maurizio Chiaramonte and Miguel A. Otaduy (Meta Reality Labs Research)\n
 \nThis paper presents a learning-based method for the simulation of rich c
 ontact deformations on reduced deformation models. Previous works learn de
 formation models for specific pairs of objects, and we lift this limitatio
 n by designing a neural model that supports general rigid collider shapes.
  We do this by formulating a novel collider descriptor that characterizes 
 local collider geometry in a region of interest. The paper shows that the 
 learning-based deformation model can be trained on a library of colliders,
  but it accurately supports unseen collider shapes at runtime. We showcase
  our method on interactive dynamic simulations with animation of rich defo
 rmation detail, manipulation and exploration of untrained objects, and aug
 mentation of contact information suitable for high-fidelity haptics.\n\nRe
 gistration Category: Full Access\n\nSession Chair: Tao Du (Tsinghua Univer
 sity, Shanghai Qi Zhi Institute)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_785&sess=sess151
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