Personalized facial makeup transfer based on outline correspondence

Abstract

Most existing makeup transfer techniques focus on light makeup styles, which limits the task of makeup transfer to color manipulation issues such as eye shadow and lip gloss. However, the makeup in real life is diverse and personalized, not only the most basic foundation, eye makeup, but also the painted patterns on the face, jewelry decoration and other personalized makeup. Inspired by the painting steps of drawing the outline first and then coloring, we propose a makeup transfer network for personalized makeup, which realizes face makeup transfer by learning outline correspondence. Specifically, we propose the outline feature extraction module and outline loss that can promote outline correspondence. Our network can not only transfer daily light makeup, but also complete transfer for complex facial painting patterns. Experiments show that our method can obtain visually more accurate makeup transfer results. Quantitative and qualitative experimental results show that the method proposed in this paper achieves superior results in extreme makeup transfer compared to the state‐of‐the‐art methods.

Styled and characteristic Peking opera facial makeup synthesis with Co-training and Transfer Conditional StyleGAN2

“…Among them, the Bezier curve was used to construct the vector pattern library of facial makeup, and the Free-Form Deformation(FFD) was used to realize the pattern deformation [5] [6]. Regarding the research on the two-dimensional projection of Peking opera facial makeup, video face recognition and video face tracking were used to project and cover the facial makeup on the face, and finally the Peking opera facial makeup was deformed according to different face features, while maintaining the shape of the facial makeup pattern and matching the key parts of the face [7]. Based on the depth camera, the Unity3D engine is used to conduct the research on the three-dimensional personalized modeling of Peking opera facial makeup, which is mainly using the registration and stitching of multi-frame face point clouds, the detection and tracking of face data, and the Laplacian mesh deformation algorithm to realize the three-dimensional modeling and deformation of facial makeup [8] [9].…”