西安交通大学学报（医学版）2026，Vol.47Issue(2)：224-233,10.DOI:10.7652/jdyxb202602005
基于静态和动态线索的人脸深度伪造的检测方法及其特点
A method for detecting facial depth-forge created by static and dynamic clues and its characteristics
摘要
Abstract
With the rapid development of deep learning technology and the swift rise of generative artificial intelligence,the quality of face forgery generation has continuously improved,and its potential risks of misuse have attracted increasing attention.This paper,which makes a systematic review of research in the related field,introduces the existing face deepfake detection methods and categorizes them according to detection cues into static detection methods and dynamic detection methods.Static detection methods include explicit logical inconsistency detection and deep feature discrepancy detection,which identify forgery traces by analyzing various differences between forged images or videos and authentic ones.In contrast,dynamic detection methods mainly focus on the temporal characteristics of videos and the consistency across different modalities.In addition,this paper reviews common face forgery techniques as well as widely used datasets for forged face images and videos,and conducts an in-depth discussion on active detection strategies and approaches for improving generalization capability.关键词
人脸深度伪造检测/静态检测/动态检测/伪造数据集/泛化能力Key words
face deepfake detection/static detection/dynamic detection/forgery dataset/generalization ability分类
信息技术与安全科学引用本文复制引用
孙越涵,毛施云,李慧斌..基于静态和动态线索的人脸深度伪造的检测方法及其特点[J].西安交通大学学报（医学版）,2026,47(2):224-233,10.基金项目
西安交通大学基本科研业务费自由探索与创新类项目(No.xzy012023035)Supported in part by Central University Basic Research Fund of China(No.xzy012023035) （No.xzy012023035）
