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.