信息安全研究2025，Vol.11Issue(3)：231-240,10.DOI:10.12379/j.issn.2096-1057.2025.03.05
基于ConvNeXt的伪造人脸检测方法
Fake Face Detection Method Based on ConvNeXt
摘要
Abstract
The fake images generated by deep generative models are becoming increasingly realistic,surpassing the human eye's ability to detect them.These models have become new tools for illegal activities,such as fabricating lies and creating public opinion.Although current researchers have proposed many detection methods to detect fake images,their generalization ability is typically limited.To address this issue,we proposed a fake face detection method based on ConvNeXt.Firstly,we add a PSA(polarization self-attention)module after the second and third downsampling modules of ConvNeXt,enhancing the network's spatial and channel attention performance.Secondly,a RIB(rich imformation block)is designed at the end of ConvNeXt to enrich the information learned by the network.The information is processed through this module before final classification.Furthermore,the loss function used in network training is a combination of CrossEntropy loss and KL(Kullback-Leibler)divergence.Extensive experiments on the current mainstream fake face datasets demonstrate that our method surpasses all comparative methods in accuracy and generalization on the FF++C23 dataset.关键词
神经网络/深度学习/伪造人脸/特征提取/伪造图像检测Key words
neural network/deep learning/fake face/feature extraction/fake image detection分类
计算机与自动化引用本文复制引用
何德芬,江倩,金鑫,冯明,苗圣法,易华松..基于ConvNeXt的伪造人脸检测方法[J].信息安全研究,2025,11(3):231-240,10.基金项目
国家自然科学基金项目(62101481,62261060) （62101481,62261060）
云南省基础研究计划项目(202401AT070470,202301AW070007,202201AU070033,202201AT070112,202301AU070210) （202401AT070470,202301AW070007,202201AU070033,202201AT070112,202301AU070210）
云南省科技厅重大科技专项(202202AD080002) （202202AD080002）
云南省迟学斌专家工作站项目(202305AF150078) （202305AF150078）
