This paper proposed a novel approach to generate face caricatures automatically from a single portrait image. We decompose the process of 3D face caricatures generation into two independent subtasks: appearance transfer of texture and the geometry transfer of mesh. For the appearance transfer, we design a GAN-based network named CariFaceGAN to learn the style mapping from portrait to caricature, in which facial features are leveraged to preserve identity consistency. For geometry transfer, we first learn the transformation of the landmarks between portraits and caricatures in an embedded space obtained with Locally Linear Embedding method, and then Kriging interpolation is used to manipulate the portrait mesh constructed from a single image. The experimental results show that our proposed CariFaceGAN outperforms the state-of-the-art methods in terms of maintaining identity consistency and providing satisfactory visual effects.

本文提出了一种从单幅肖像图像自动生成面部漫画的新颖方法。我们将3D面部漫画的生成过程分解为两个独立的子任务：纹理的外观传递和网格的几何传递。对于外观转移，我们设计了一个基于GAN的网络CariFaceGAN，以学习从肖像到漫画的样式映射，其中利用了面部特征来保持身份一致性。对于几何传递，我们首先学习使用局部线性嵌入方法获得的嵌入式空间中人像和漫画之间的地标转换，然后使用Kriging插值来处理由单个图像构造的人像网格。