Recent advances in deep learning have led to substantial improvements in deepfake generation, resulting in fake media with a more realistic appearance. Although deepfake media have potential application in a wide range of areas and are drawing much attention from both the academic and industrial communities, it also leads to serious social and criminal concerns. This chapter explores the evolution of and challenges in deepfake generation and detection. It also discusses possible ways to improve the robustness of deepfake detection for a wide variety of media (e.g., in-the-wild images and videos). Finally, it suggests a focus for future fake media research.
翻译:最近深层学习的进展导致深层假象一代的大幅进步,导致假象媒体出现更现实的外观,尽管深层假象媒体有可能在广泛领域应用,并引起学术界和产业界的极大关注,但也引起了严重的社会和犯罪关注,本章探讨了深层假象一代的演变和发现方面的挑战,还探讨了提高深层假象探测能力,供各种媒体(如现场图像和视频)使用的各种可能途径,最后,它提出了未来假象媒体研究的重点。