【摘要】 近年来，视频媒体随着移动互联网的普及发展迅猛，与此同时人脸伪造技术也随着计算机视觉的发展取得了很大的进步.诚然人脸伪造可以用来制作有趣的短视频应用，但由于其易生成、生成用时短、逼真度高等特性，其恶意使用对社会稳定和信息安全产生了极大威胁，如何检测互联网中的人脸伪造视频成为亟待解决的问题.在国内外学者的努力下，伪造检测在近些年也取得了很大的突破，因此旨在对现有的伪造检测方法进行详细的梳理和总结.特别地，首先介绍伪造检测数据集，然后从伪造视频的痕迹、神经网络结构、视频时序信息、人脸身份信息、检测算法泛化性等方面对现有的方法进行归纳和总结，并对相应方法的检测结果进行对比和分析，最后对深度伪造检测的研究现状进行总结，并展望其面临的挑战和发展趋势，为相关研究工作提供借鉴.更多还原

【Abstract】 Video media has developed rapidly with the popularity of the mobile Internet in recent years. At the same time, face forgery technology has also made great progress with the development of computer vision. Face forgery technology can be adopted to make interesting short video applications, but due to characteristics such as high fidelity, easy and quick generation, its malicious use poses a great threat to social stability and information security. Therefore, how to detect fake videos of faces in the Internet has become an urgent problem to be solved. With the efforts of scholars in the world, forgery detection has also made great breakthroughs in recent years. Therefore, this review aims to summarize the existing forgery detection methods in detail. In particular, we first introduce the forgery detection data set, and then summarizes the existing methods from the aspects of forgery video trace, neural network architecture, temporal information of videos, face identity information, and generalization of detection algorithms. Then we compare and analyze their corresponding detection results. Finally, we summarize the research directions and existing problems of deep forgery detection and discusses the challenges and development trends, so that which can provide reference for relevant research.更多还原