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/.

翻译：三维虚拟角色的建模有益于AR/VR、游戏和影视等多种应用场景。作为虚拟角色的重要组成部分，面部特征为角色赋予了丰富的多样性和生动性。然而，即便对于经验丰富的艺术家而言，使用商业工具构建三维角色面部模型通常需要繁重的工作量。现有各类基于草图的工具无法支持非专业人士建模多样化的面部形状和丰富的几何细节。本文提出SketchMetaFace——一个面向业余用户的草图系统，能在数分钟内完成高保真三维面部建模。我们精心设计了用户界面和底层算法。首先，采用曲率感知线条以更好地支持面部细节雕刻的可控性。其次，针对将二维草图映射到三维模型的关键问题，我们开发了一种名为"隐式与深度引导网格建模"（IDGMM）的新型学习方法。该方法融合了网格、隐式和深度表示的优势，以高效实现高质量结果。此外，为进一步提升可用性，我们提出了从粗到细的二维草图界面设计以及数据驱动的线条建议工具。用户研究证明了我们的系统在易用性和结果视觉质量方面优于现有建模工具。实验分析也表明IDGMM在精度与效率之间取得了更优的平衡。SketchMetaFace可通过 https://zhongjinluo.github.io/SketchMetaFace/ 获取。