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DTSTAMP:20260114T163632Z
LOCATION:Darling Harbour Theatre\, Level 2 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T093000
DTEND;TZID=Australia/Melbourne:20231212T124500
UID:siggraphasia_SIGGRAPH Asia 2023_sess209_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, Enhanced Access, Trade Exhibitor, Experi
 ence Hall Exhibitor\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_785&sess=sess209
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