SketchMetaFace：一种基于学习的草图界面，用于高保真度的3D角色面部建模。

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

July 3, 2023

作者: Zhongjin Luo, Dong Du, Heming Zhu, Yizhou Yu, Hongbo Fu, Xiaoguang Han

cs.AI

摘要

建模3D头像有益于各种应用场景，如增强现实/虚拟现实、游戏和拍摄。角色面孔作为头像的重要组成部分，为头像增添了显著的多样性和生动性。然而，构建3D角色面部模型通常需要使用商业工具进行大量工作，即使对于经验丰富的艺术家也是如此。各种现有的基于草图的工具未能支持业余用户建模多样化的面部形状和丰富的几何细节。本文介绍了SketchMetaFace - 一个针对业余用户设计的草图系统，可在几分钟内建模高保真的3D面部。我们精心设计了用户界面和底层算法。首先，采用了曲率感知笔画，以更好地支持雕刻面部细节的可控性。其次，考虑到将2D草图映射到3D模型的关键问题，我们开发了一种名为“隐式和深度引导网格建模”（IDGMM）的新颖基于学习的方法。它融合了网格、隐式和深度表示的优势，以实现高质量和高效率的结果。此外，为了进一步支持可用性，我们提出了一个由粗到细的2D草图界面设计和一个数据驱动的笔画建议工具。用户研究表明，我们的系统在易用性和视觉质量方面优于现有建模工具。实验分析还显示，IDGMM在精度和效率之间取得了更好的折衷。SketchMetaFace可在https://zhongjinluo.github.io/SketchMetaFace/ 上获得。

English

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/.