Converting Real Human Avatar to Cartoon Avatar using CycleGAN

Abstract

Cartoons are an important art style, which not only has a unique drawing effect but also reflects the character itself, which is gradually loved by people. With the development of image processing technology, people's research on image research is no longer limited to image recognition, target detection, and tracking, but also images In this paper, we use deep learning based image processing to generate cartoon caricatures of human faces. Therefore, this paper investigates the use of deep learning-based methods to learn face features and convert image styles while preserving the original content features, to automatically generate natural cartoon avatars. In this paper, we study a face cartoon generation method based on content invariance. In the task of image style conversion, the content is fused with different style features based on the invariance of content information, to achieve the style conversion.