论文标题
当地的面部化妆转移通过分离的表示
Local Facial Makeup Transfer via Disentangled Representation
论文作者
论文摘要
面部化妆转移的目的是在保留面部身份的同时，在任意给定的化妆中以任意给定的化妆形象呈现非制作面部图像。最先进的方法将化妆样式信息与面部图像分开，以实现化妆转移。但是，化妆样式包括几种仍然纠缠在一起的语义清晰的本地样式。在本文中，我们提出了一种新颖的统一对抗性分解网络，将面部图像进一步分解为四个独立的组件，即个人身份，嘴唇化妆样式，眼睛化妆样式和脸部化妆风格。由于进一步的化妆样式，我们的方法不仅可以控制全球化妆样式的程度，而且可以灵活地调节任何其他方法无法做到的本地化妆样式的程度。对于化妆去除，与其他方法不同的方法将化妆去除是化妆的反向过程，我们将化妆转移与化妆的去除整合到一个均匀的框架中，并获得多个化妆去除结果。广泛的实验表明，与最先进的方法相比，我们的方法可以产生更现实和准确的化妆转移结果。
Facial makeup transfer aims to render a non-makeup face image in an arbitrary given makeup one while preserving face identity. The most advanced method separates makeup style information from face images to realize makeup transfer. However, makeup style includes several semantic clear local styles which are still entangled together. In this paper, we propose a novel unified adversarial disentangling network to further decompose face images into four independent components, i.e., personal identity, lips makeup style, eyes makeup style and face makeup style. Owing to the further disentangling of makeup style, our method can not only control the degree of global makeup style, but also flexibly regulate the degree of local makeup styles which any other approaches can't do. For makeup removal, different from other methods which regard makeup removal as the reverse process of makeup, we integrate the makeup transfer with the makeup removal into one uniform framework and obtain multiple makeup removal results. Extensive experiments have demonstrated that our approach can produce more realistic and accurate makeup transfer results compared to the state-of-the-art methods.
