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杨睿, 胡心如, 黄卓超, 张玉书, 蓝如师, 邓珍荣, 罗笑南. 深度网络生成式伪造人脸检测方法研究综述[J]. 计算机辅助设计与图形学学报. DOI: 10.3724/SP.J.1089.null.2023-00615
引用本文: 杨睿, 胡心如, 黄卓超, 张玉书, 蓝如师, 邓珍荣, 罗笑南. 深度网络生成式伪造人脸检测方法研究综述[J]. 计算机辅助设计与图形学学报. DOI: 10.3724/SP.J.1089.null.2023-00615
Rui Yang, Xinru Hu, Zhuochao Huang, Yushu Zhang, Rushi Lan, Zhenrong Deng, Xiaonan Luo. Review of Deep Network Generative Fake Face Detection Methods[J]. Journal of Computer-Aided Design & Computer Graphics. DOI: 10.3724/SP.J.1089.null.2023-00615
Citation: Rui Yang, Xinru Hu, Zhuochao Huang, Yushu Zhang, Rushi Lan, Zhenrong Deng, Xiaonan Luo. Review of Deep Network Generative Fake Face Detection Methods[J]. Journal of Computer-Aided Design & Computer Graphics. DOI: 10.3724/SP.J.1089.null.2023-00615

深度网络生成式伪造人脸检测方法研究综述

Review of Deep Network Generative Fake Face Detection Methods

  • 摘要: 随着深度网络生成式伪造人脸技术的迅速传播, 不法分子通过伪造人脸图像和视频实施电信诈骗、操纵舆论、传播淫秽等目的, 如何从海量数据中高效准确地检测出伪造人脸成为研究焦点. 本文从深度网络生成式伪造人脸图像和生成式伪造人脸视频两个领域出发, 系统归纳、分析、比较了当前深度网络生成式伪造人脸检测方法. 针对伪造人脸图像, 本文从基于数字图像处理基础、深层次特征提取、空间域特征分析、多特征融合分析、指纹检测等五个类别详细介绍了检测方法. 此外还从生理信号、身份信息、多模态、时空不一致四个类别, 对伪造人脸视频的检测方法进行了探讨. 本文的研究总结对于防范虚假信息的传播、保护个人隐私和维护社会公正具有重要意义.

     

    Abstract: With the rapid spread of deep network generated fake face technology, criminals fake face images and videos to implement telecommunications fraud, manipulate public opinion, disseminate obscenity and other purposes. How to efficiently and accurately detect fake faces from massive data has become a research focus. In this paper, we systematically summarize, analyze and compare the current deep network generative forgery face detection methods from two fields: generative forgery face image and generative forgery face video. For forged face images, this paper introduces the detection methods in detail from five categories: based on digital image processing foundation, deep feature extraction, spatial domain feature analysis, multi-feature fusion analysis, and fingerprint detection. In addition, the detection methods of fake face videos are discussed from four categories: physiological signals, identity information, multi-modal and spatio-temporal inconsistency. The research summary of this paper is of great significance for preventing the spread of false information, protecting personal privacy and maintaining social justice.

     

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