  Generating faithful visualizations of human faces requires capturing both
coarse and fine-level details of the face geometry and appearance. Existing
methods are either data-driven, requiring an extensive corpus of data not
publicly accessible to the research community, or fail to capture fine details
because they rely on geometric face models that cannot represent fine-grained
details in texture with a mesh discretization and linear deformation designed
to model only a coarse face geometry. We introduce a method that bridges this
gap by drawing inspiration from traditional computer graphics techniques.
Unseen expressions are modeled by blending appearance from a sparse set of
extreme poses. This blending is performed by measuring local volumetric changes
in those expressions and locally reproducing their appearance whenever a
similar expression is performed at test time. We show that our method
generalizes to unseen expressions, adding fine-grained effects on top of smooth
volumetric deformations of a face, and demonstrate how it generalizes beyond
faces.
