ISSN 1000-1239 CN 11-1777/TP

• 图形图像 •

### 一种基于局部属性生成对抗网络的人脸修复算法

1. (湖南大学信息科学与工程学院 长沙 410082) (jiangbin@hnu.edu.cn)
• 出版日期: 2019-11-12
• 基金资助:
国家自然科学基金项目(61702176)；湖南省自然科学基金项目(2017JJ3038)

### A Face Inpainting Algorithm with Local Attribute Generative Adversarial Networks

Jiang Bin, Liu Hongyu, Yang Chao, Tu Wenxuan, Zhao Zilong

1. (College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082)
• Online: 2019-11-12

Abstract: Recent researches in neural network models have shown great potential in image inpainting task, which focuses on understanding image semantic information and reconstructs missing image content. These researches can generate visually reasonable image structures and textures, however, they usually produce distorted structures or blurry textures that are inconsistent with the surrounding areas, especially for the face inpainting task. The face inpainting task is often necessary to gene the advantages of fully connected convolution and U-net network, and the model proposes locally attributes discriminator to make the inpainted contents more innovative and is able to keep the global and local semantic consistency. The model not only improves the perception of the overall semantic information of the face image, but also restores the key parts of the face based on the local attributes. Experiments on the CelebA dataset have shown that our model can effectively deal with face image repair problems and generate novel results.