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DTSTAMP:20240214T070248Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T091000
DTEND;TZID=Australia/Melbourne:20231215T092500
UID:siggraphasia_SIGGRAPH Asia 2023_sess134_papers_937@linklings.com
SUMMARY:Variational Barycentric Coordinates
DESCRIPTION:Technical Papers\n\nAna Dodik (MIT CSAIL); Oded Stein (Univers
 ity of Southern California, MIT CSAIL); and Vincent SItzmann and Justin So
 lomon (MIT CSAIL)\n\nWe propose a variational technique to optimize for ge
 neralized barycentric coordinates that offers additional artistic control 
 compared to existing models. Prior work represents barycentric coordinates
  using meshes or closed-form formulae, in practice limiting the choice of 
 objective function. In contrast, we directly parameterize the continuous f
 unction that maps any coordinate in a polytope's interior to its barycentr
 ic coordinates using a neural field. This formulation is enabled by our th
 eoretical characterization of barycentric coordinates, which allows us to 
 construct neural fields that parameterize the entire function class of val
 id coordinates. We demonstrate the flexibility of our model using a variet
 y of objective functions, including multiple smoothness and deformation-aw
 are energies; as a side contribution, we also present mathematically-justi
 fied means of measuring and minimizing objectives like total variation on 
 discontinuous neural fields. We offer a practical acceleration strategy, p
 resent a thorough validation of our algorithm, and demonstrate several app
 lications.\n\nRegistration Category: Full Access\n\nSession Chair: Juno Ki
 m (University of New South Wales)
URL:https://asia.siggraph.org/2023/full-program?id=papers_937&sess=sess134
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