A Survey of Audiovisual Deepfake Detection Techniques

Abstract

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.