A Review of Deep Learning-based Approaches for Deepfake Content Detection

arXiv:2202.06095v3 Announce Type: replace
Abstract: Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's integrity and can lead to social instability. To address this issue, there is a pressing need to develop new computational models that can efficiently detect forged content and alert users to potential image and video manipulations. This paper presents a comprehensive review of recent studies for deepfake content detection …

abstract arxiv concerns counterfeit cs.ai cs.cv deepfake deep learning detection generative generative models images integrity issue people review social threat type videos