The current spike of hyper-realistic faces artificially generated using deepfakes calls for
media forensics solutions that are tailored to video streams and work reliably with a low false …

Deep generative models have recently achieved impressive results for many real-world
applications, successfully generating high-resolution and diverse samples from complex …

Deepfakes is a branch of malicious techniques that transplant a target face to the original
one in videos, resulting in serious problems such as infringement of copyright, confusion of …

Recent advances in face forgery techniques produce nearly visually untraceable deepfake
videos, which could be leveraged with malicious intentions. As a result, researchers have …

Recently, Deepfake has drawn considerable public attention due to security and privacy
concerns in social media digital forensics. As the wildly spreading Deepfake videos on the …

Face manipulation techniques, especially DeepFake techniques, are causing severe social
concerns and security problems. When faced with skewed data distributions such as those …

In this paper, we focus on identifying the limitations and shortcomings of existing deepfake
detection frameworks. We identified some key problems surrounding deepfake detection …

Benefitting from the development of deep generative networks, modern fake news
generation methods called Deepfake rapidly go viral over the Internet, calling for efficient …

Face forgery by deepfake is widely spread over the internet and this raises severe societal
concerns. In this paper, we propose a novel video transformer with incremental learning for …

The rapid development of facial manipulation techniques has aroused public concerns in
recent years. Existing deepfake video detection approaches attempt to capture the discrim …