视听觉深度伪造检测技术研究综述

A Survey of Audiovisual Deepfake Detection Techniques

深度学习被广泛应用于自然语言处理、计算机视觉和无人驾驶等领域,引领了新一轮的人工智能浪潮。然而,深度学习也被用于构建对国家安全、社会稳定和个人隐私等造成潜在威胁的技术,如近期在世界范围内引起广泛关注的深度伪造技术能够生成逼真的虚假图像及音视频内容。本文介绍了深度伪造的背景及深度伪造内容生成原理,概述和分析了针对不同类型伪造内容(图像、视频、音频等)的检测方法和数据集,最后展望了深度伪造检测和防御未来的研究方向和面临的挑战。

Deep learning has been widely used in fields such as natural language processing,computer vision,and driverless vehicles,leading a new wave of artificial intelligence.Deep learning advances however have also been used to create technologies that pose potential threats to national security,social stability,and personal privacy.For example,deepfakes that have recently attracted widespread attention worldwide,which could generate seemingly realistic fake images,audio and video content.This article introduces the background of deepfakes and the principles of deepfakes creation,and then outlines and analyzes the detection methods and datasets for different types of deepfakes,including images,videos,audios,etc.Finally,the article discusses potential research directions and challenges of deepfakes detection and prevention.