A Face Replacement Neural Network for Image and Video

Abstract

We propose a method to solve the problem of face replacing for image and video. This approach is enabled to transform an input identity into a target identity, including the facial expression, facial organs and the facial skin colour. To this end, we make the following contributions. (a)We elaborately design a simple auto encoder network to reconstruct the face. (b)Building on recent research in this area, we integrate a weight mask into the loss function to improve the performance of the network during training. (c)Unlike the previous work, we can transform the face not only in image, but also merging video after we adjust the results. We make it easier to replace a people's face with another one in image or video by combining neural networks with simple processing steps.