计算机与现代化Issue(4)：38-42,5.DOI:10.3969/j.issn.1006-2475.2024.04.007
基于I-ConvNeXt的GAN生成人脸图像鉴别方法
GAN-generated Fake Images Recognition Based on Improved ConvNeXt
摘要
Abstract
In order to distinguish the authenticity of face images in social networks,a recognition method based on ConvNeXt for face image generated by Generative adversarial networks(GAN)is proposed.The ConvNeXt network structure is used as the main body,using the color features and spatial texture features of the face image,and multi-channel combination input(Multi-channel Input,MCI)with multi-color space is used to expand the learning range of the network,while channel attention mecha-nism and spatial attention mechanism are introduced to highlight the differences between real and fake face images in color com-ponents and spatial features,and then the detection and recognition of fake face images are achieved.The experimental results show that the recognition accuracy of face images generated by GAN with improved ConvNeXt(I-ConvNeXt)network structure reaches 99.405%,with an average accuracy improvement of 1.455 percentage points compared with the original ConvNeXt algo-rithm.The results validate the feasibility and reasonableness of the proposed scheme.关键词
生成式对抗网络/注意力机制/颜色特征/生成人脸/多通道输入Key words
generative adversarial network/attention mechanism/color features/generated face image/multi-channel input分类
信息技术与安全科学引用本文复制引用
肖梦思,吴建斌,涂雅蒙,袁林锋..基于I-ConvNeXt的GAN生成人脸图像鉴别方法[J].计算机与现代化,2024,(4):38-42,5.基金项目
国家自然科学基金资助项目(U1736121) （U1736121）
中央高校基本科研业务费专项资金资助项目(CCNU22JC024) （CCNU22JC024）
