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 is available at https://zhongjinluo.github.io/SketchMetaFace/.

翻译：建模3D虚拟角色可惠及AR/VR、游戏与影视等多种应用场景。作为虚拟角色的核心组成部分，面部特征贡献了显著的多样性与生动性。然而，即使对于经验丰富的艺术家，使用商用工具构建3D角色面部模型通常需要繁重的工作量。现有基于草图的工具难以支持业余用户建模多样化的面部形状与丰富的几何细节。本文提出SketchMetaFace——一套面向业余用户的草图系统，可在数分钟内完成高保真3D面部建模。我们精心设计了用户界面与底层算法。首先，采用曲率感知笔触以增强面部细节雕刻的可控性。其次，针对二维草图映射至三维模型这一关键问题，我们开发了名为“隐式与深度引导的网格建模”（IDGMM）的新型学习方法。该方法融合网格、隐式与深度表征的优势，以高计算效率实现高质量结果。此外，为提升可用性，我们提出了由粗到精的二维草图界面设计及数据驱动的笔触建议工具。用户研究表明，本系统在易用性与结果视觉质量上均优于现有建模工具。实验分析亦显示IDGMM在精度与效率之间取得了更优平衡。SketchMetaFace开源地址：https://zhongjinluo.github.io/SketchMetaFace/。