title: BlendFields: Few-Shot Example-Driven Facial Modeling
summary: 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.
paper_authors._id: 6461ab88846a6c8c830508c9
paper_authors.name: Kacper Kania
paper_authors._id: 6461ab88846a6c8c830508ca
paper_authors.name: Stephan J. Garbin
paper_authors._id: 6461ab88846a6c8c830508cb
paper_authors.name: Andrea Tagliasacchi
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-05-16T15:56:34.101Z
paper_authors._id: 6310c97fa23f0327bce7f93d
paper_authors.avatarUrl: /avatars/999c12348ce57d71f15337f50a6b2685.svg
paper_authors.fullname: Andrea
paper_authors.type: user
paper_authors.user: taiya
paper_authors._id: 6461ab88846a6c8c830508cc
paper_authors.name: Virginia Estellers
paper_authors._id: 6461ab88846a6c8c830508cd
paper_authors.name: Kwang Moo Yi
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-05T18:56:58.345Z
paper_authors._id: 64a591af9b8ae9ccccfdd3e7
paper_authors.avatarUrl: /avatars/c6cd43d814956261639fe594bc4aa181.svg
paper_authors.fullname: Kwang Moo Yi
paper_authors.type: user
paper_authors.user: kmyi
paper_authors._id: 6461ab88846a6c8c830508ce
paper_authors.name: Julien Valentin
paper_authors._id: 6461ab88846a6c8c830508cf
paper_authors.name: Tomasz Trzciński
paper_authors._id: 6461ab88846a6c8c830508d0
paper_authors.name: Marek Kowalski
paper_title: BlendFields: Few-Shot Example-Driven Facial Modeling
paper_summary: 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.
paper_ai_summary: A novel method blends appearance from a limited set of extreme poses to capture fine details in face geometry and appearance, using local volumetric changes to generalize to unseen expressions.
paper_ai_keywords: geometric face models mesh discretization linear deformation computer graphics techniques extreme poses local volumetric changes unseen expressions fine-grained details