湖北民族大学学报（自然科学版）2025，Vol.43Issue(2)：217-223,258,8.DOI:10.13501/j.cnki.42-1908/n.2025.06.018
基于GradGR多源特征融合的面部伪造检测方法
Face Forgery Detection Method Based on Multi-source Features Fusion of GradGR
摘要
Abstract
To address the issue that the existing face forgery detection methods performed well on specific forgery operations but had obvious deficiencies in cross-dataset generalization ability,a face forgery detection model based on image gradient-guided reconstruction(GradGR)was proposed.This model constructed an auxiliary gradient reconstruction branch on top of the original image reconstruction backbone.Through a feature transfer mechanism,the intermediate features of this branch were used to guide the backbone to focus on the forged region revealed by the gradient.In addition,a multi-source feature fusion(MSFF)module was included in the GradGR model,which effectively enhanced cross-layer feature interactions and markedly improved the efficiency of feature fusion by integrating codec intermediate features with two-way reconstruction differences.The results demonstrated that the GradGR model not only achieved the optimal level within the datasets but also improved the average cross-dataset accuracy by nearly 3.22%compared with the extreme inception(Xception)model.This model provided a new research idea for face forgery detection.关键词
面部伪造检测/深度学习/计算机视觉/图像重建学习/图像梯度/多源特征融合Key words
facial forgery detection/deep learning/computer vision/image reconstruction learning/image gradient/multi-source feature fusion分类
计算机与自动化引用本文复制引用
韩栋宇,郭婷,杨高明,朱鹏,宋一帆..基于GradGR多源特征融合的面部伪造检测方法[J].湖北民族大学学报（自然科学版）,2025,43(2):217-223,258,8.基金项目
国家自然科学基金项目(52374155) （52374155）
安徽自然科学基金项目(2308085MF218) （2308085MF218）
安徽高等学校科学研究项目(2022AH040113) （2022AH040113）
安徽理工大学医学专项培育项目(YZ2023H2B007) （YZ2023H2B007）
福建医疗大数据工程重点实验室开放基金项目(KLKF202302) （KLKF202302）
安徽理工大学研究生创新基金项目(2024CX2116). （2024CX2116）
