title: SketchMetaFace: A Learning-based Sketching Interface for High-fidelity
    3D Character Face Modeling
summary: Modeling 3D avatars benefits various application scenarios such as AR/VR,
  gaming, and filming. Character faces contribute significant diversity and
  vividity as a vital component of avatars. However, building 3D character face
  models usually requires a heavy workload with commercial tools, even for
  experienced artists. Various existing sketch-based tools fail to support
  amateurs in modeling diverse facial shapes and rich geometric details. In this
  paper, we present SketchMetaFace - a sketching system targeting amateur users
  to model high-fidelity 3D faces in minutes. We carefully design both the user
  interface and the underlying algorithm. First, curvature-aware strokes are
  adopted to better support the controllability of carving facial details.
  Second, considering the key problem of mapping a 2D sketch map to a 3D model,
  we develop a novel learning-based method termed "Implicit and Depth Guided Mesh
  Modeling" (IDGMM). It fuses the advantages of mesh, implicit, and depth
  representations to achieve high-quality results with high efficiency. In
  addition, to further support usability, we present a coarse-to-fine 2D
  sketching interface design and a data-driven stroke suggestion tool. User
  studies demonstrate the superiority of our system over existing modeling tools
  in terms of the ease to use and visual quality of results. Experimental
  analyses also show that IDGMM reaches a better trade-off between accuracy and
  efficiency. SketchMetaFace are available at
  https://zhongjinluo.github.io/SketchMetaFace/.
paper_authors._id: 64a3a49f50091725077b800f
paper_authors.name: Zhongjin Luo
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-05T18:56:01.487Z
paper_authors._id: 63a31e22a0ed04b823c01015
paper_authors.avatarUrl: /avatars/455f2de6dab9504c154dad708a1fb74d.svg
paper_authors.fullname: Zhongjin
paper_authors.type: user
paper_authors.user: xiaojin66
paper_authors._id: 64a3a49f50091725077b8010
paper_authors.name: Dong Du
paper_authors._id: 64a3a49f50091725077b8011
paper_authors.name: Heming Zhu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-04T19:16:34.483Z
paper_authors._id: 64a41b3da3f7783f6c13bced
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/64a41b3da3f7783f6c13bced/M-w8PUAs64hG2IRguZuf7.jpeg
paper_authors.fullname: Heming  Zhu
paper_authors.type: user
paper_authors.user: kv2000
paper_authors._id: 64a3a49f50091725077b8012
paper_authors.name: Yizhou Yu
paper_authors._id: 64a3a49f50091725077b8013
paper_authors.name: Hongbo Fu
paper_authors._id: 64a3a49f50091725077b8014
paper_authors.name: Xiaoguang Han
paper_title: SketchMetaFace: A Learning-based Sketching Interface for High-fidelity
    3D Character Face Modeling
paper_summary: Modeling 3D avatars benefits various application scenarios such as AR/VR,
  gaming, and filming. Character faces contribute significant diversity and
  vividity as a vital component of avatars. However, building 3D character face
  models usually requires a heavy workload with commercial tools, even for
  experienced artists. Various existing sketch-based tools fail to support
  amateurs in modeling diverse facial shapes and rich geometric details. In this
  paper, we present SketchMetaFace - a sketching system targeting amateur users
  to model high-fidelity 3D faces in minutes. We carefully design both the user
  interface and the underlying algorithm. First, curvature-aware strokes are
  adopted to better support the controllability of carving facial details.
  Second, considering the key problem of mapping a 2D sketch map to a 3D model,
  we develop a novel learning-based method termed "Implicit and Depth Guided Mesh
  Modeling" (IDGMM). It fuses the advantages of mesh, implicit, and depth
  representations to achieve high-quality results with high efficiency. In
  addition, to further support usability, we present a coarse-to-fine 2D
  sketching interface design and a data-driven stroke suggestion tool. User
  studies demonstrate the superiority of our system over existing modeling tools
  in terms of the ease to use and visual quality of results. Experimental
  analyses also show that IDGMM reaches a better trade-off between accuracy and
  efficiency. SketchMetaFace are available at
  https://zhongjinluo.github.io/SketchMetaFace/.
paper_ai_summary: A sketch-based system called SketchMetaFace enables amateur users to model high-fidelity 3D faces efficiently by using curvature-aware strokes and a novel method called Implicit and Depth Guided Mesh Modeling (IDGMM).
paper_ai_keywords: curvature-aware strokes Implicit and Depth Guided Mesh Modeling IDGMM mesh representations implicit representations depth representations coarse-to-fine data-driven stroke suggestions