Realistic Hair Style Try-On: Face and Hair Image Mapping Using Semantic Maps for SDEdit

Machine learning-based image generation can create new person face images with new hair colors or hairstyles. This paper presents synthesis and editing method to modify hairstyles in the images by semantic maps. The face and hair images are mapped and inpainted using fast marching method and Stochastic Differential Editing (SDEdit). The experimental results shows that the proposed method controls both hairstyles and color effectively with single target hairstyle image. Moreover, the method is able to generate hairstyles in case of occluded face images.