Deep learning for face image synthesis and semantic manipulations: a review and future perspectives

摘要

Image synthesis using representations learned by deep neural networks has gained wide attention in recent years. Among the different categories of natural images, face images are very important because of their broad range of applications. However, it is very challenging to synthesize face images due to their highly complicated hierarchical structure and the uniqueness of information contained in individual face images. This paper aims at providing a comprehensive review of the recent developments and applications of face synthesis and semantic manipulations using deep learning and discusses future perspectives for improving face perception.