重庆工商大学学报（自然科学版）2025，Vol.42Issue(4)：80-87,8.DOI:10.16055/j.issn.1672-058X.2025.0004.010
基于操纵痕迹融合的人脸伪造检测方法
Face Forgery Detection Method Based on Manipulation Trace Fusion
摘要
Abstract
Objective In view of the current lack of a powerful fake face detection model that can expose fake face images in complex scenes,a new network called two-stream manipulation trace network(TSMTN)is proposed for learning subtle manipulation traces on facial regions in fake images.Methods This method is different from the previous methods of directly learning features from images.Instead,it first extracts manipulation traces from the image and then uses the manipulation traces to detect whether the face has been manipulated.The network consists of three key modules:spatial domain manipulation trace extraction(SDMTE),frequency domain manipulation trace extraction(FDMTE)and feature fusion module(FFM)based on self-attention mechanism.SDMTE uses convolutional neural networks(CNNs)to learn subtle manipulation traces in the image spatial domain.FDMTE learns the manipulation traces of high-frequency information in the frequency domain of images.FFM fuses manipulation traces in the spatial and frequency domains to generate final features for classification.Results The experimental results show that the model has good performance and has reached an advanced level on commonly used detection datasets.Conclusion This method shows good robustness and generalization ability and has made some progress,which is of great significance.关键词
人脸检测/操纵痕迹/空间域/频域/自注意力机制Key words
face detection/manipulation traces/spatial domain/frequency domain/self-attention mechanism分类
信息技术与安全科学引用本文复制引用
黄继胜,杨高明..基于操纵痕迹融合的人脸伪造检测方法[J].重庆工商大学学报（自然科学版）,2025,42(4):80-87,8.基金项目
安徽省自然科学基金(2008085MF220). （2008085MF220）
