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DTSTAMP:20240214T070248Z
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:Technical Papers\n\nCristian Romero and Dan Casas (Universidad
  Rey Juan Carlos) and Maurizio Chiaramonte and Miguel A. Otaduy (Meta Real
 ity Labs Research)\n\nThis paper presents a learning-based method for the 
 simulation of rich contact deformations on reduced deformation models. Pre
 vious works learn deformation models for specific pairs of objects, and we
  lift this limitation by designing a neural model that supports general ri
 gid collider shapes. We do this by formulating a novel collider descriptor
  that characterizes local collider geometry in a region of interest. The p
 aper shows that the learning-based deformation model can be trained on a l
 ibrary of colliders, but it accurately supports unseen collider shapes at 
 runtime. We showcase our method on interactive dynamic simulations with an
 imation of rich deformation detail, manipulation and exploration of untrai
 ned objects, and augmentation of contact information suitable for high-fid
 elity haptics.\n\nRegistration Category: Full Access\n\nSession Chair: Tao
  Du (Tsinghua University, Shanghai Qi Zhi Institute)
URL:https://asia.siggraph.org/2023/full-program?id=papers_785&sess=sess151
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