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DTSTAMP:20240214T070240Z
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_327@linklings.com
SUMMARY:An Implicit Physical Face Model Driven by Expression and Style
DESCRIPTION:Technical Papers\n\nLingchen Yang (ETH Zürich); Gaspard Zoss a
 nd Prashanth Chandran (The Walt Disney Company (Switzerland) GmbH); Paulo 
 Gotardo (Disney Research Studios, The Walt Disney Company (Switzerland) Gm
 bH); Markus Gross (ETH Zürich, The Walt Disney Company (Switzerland) GmbH)
 ; Barbara Solenthaler (ETH Zürich); Eftychios Sifakis (University of Wisco
 nsin Madison); and Derek Bradley (The Walt Disney Company (Switzerland) Gm
 bH)\n\n3D facial animation is often produced by manipulating facial deform
 ation models (or rigs), that are traditionally parameterized by expression
  controls. A key component that is usually overlooked is expression ``styl
 e", as in, how a particular expression is performed. Although it is common
  to define a semantic basis of expressions that characters can perform, mo
 st characters perform each expression in their own style. To date, style i
 s usually entangled with the expression, and it is not possible to transfe
 r the style of one character to another when considering facial animation.
  We present a new face model, based on a data-driven implicit neural physi
 cs model, that can be driven by both expression and style separately. At t
 he core, we present a framework for learning implicit physics-based actuat
 ions for multiple subjects simultaneously, trained on a few arbitrary perf
 ormance capture sequences from a small set of identities. Once trained, ou
 r method allows generalized physics-based facial animation for any of the 
 trained identities, extending to unseen performances. Furthermore, it gran
 ts control over the animation style, enabling style transfer from one char
 acter to another or blending styles of different characters. Lastly, as a 
 physics-based model, it is capable of synthesizing physical effects, such 
 as collision handling, setting our method apart from conventional approach
 es.\n\nRegistration Category: Full Access, Enhanced Access, Trade Exhibito
 r, Experience Hall Exhibitor
URL:https://asia.siggraph.org/2023/full-program?id=papers_327&sess=sess209
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