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Modeling 3D avatars benefits various application scenarios such as AR/VR,gaming, and filming. Character faces contribute significant diversity andvividity as a vital component of avatars. However, building 3D character facemodels usually requires a heavy workload with commercial tools, even forexperienced artists. Various existing sketch-based tools fail to supportamateurs in modeling diverse facial shapes and rich geometric details. In thispaper, we present SketchMetaFace - a sketching system targeting amateur usersto model high-fidelity 3D faces in minutes. We carefully design both the userinterface and the underlying algorithm. First, curvature-aware strokes areadopted 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 MeshModeling" (IDGMM). It fuses the advantages of mesh, implicit, and depthrepresentations to achieve high-quality results with high efficiency. Inaddition, to further support usability, we present a coarse-to-fine 2Dsketching interface design and a data-driven stroke suggestion tool. Userstudies demonstrate the superiority of our system over existing modeling toolsin terms of the ease to use and visual quality of results. Experimentalanalyses also show that IDGMM reaches a better trade-off between accuracy andefficiency. SketchMetaFace is available athttps://zhongjinluo.github.io/SketchMetaFace/.

SketchMetaFace: A Learning-based Sketching Interface for High-fidelity 3D Character Face Modeling