基于深度学习的人脸妆容迁移算法.

Face makeup transfer refers to the task of transferring reference makeup to people’s face while keeping the features of people’s face and showing the style of the reference makeup as much as possible. The current methods of transferring facial makeup do not fully consider the facial differences,it causes the problems such as insufficient extracted facial information. In order to avoid such problems and realize automatic transferring of face makeup,this paper proposed a face makeup transfer algorithm based on deep convolutional neural network. First,the algorithm automatically located the people’s face and features of reference makeup,and extracted the feature information of key parts. After the autonomous training of deep convolutional neural network,it automatically transferred the reference makeup to people’s face through the makeup transfer network and loss function. The simulation result shows that the algorithm takes less time,has more advantages in computing performance,and makeup transfer effect is more natural without changing the details of the original facial features. [ABSTRACT FROM AUTHOR]