With technological advances, the generation of deepfake material is now within reach of
those operating consumer-grade hardware. As a result, much research has been …

DeepFake detection aims to differentiate falsified faces from real ones. Most approaches
formulate it as a binary classification problem by solely mining the local artifacts and …

With the rapid development of Deepfake techniques, the capacity of generating hyper-
realistic faces has aroused public concerns in recent years. The temporal inconsistency …

Generative deep learning techniques have invaded the public discourse recently. Despite
the advantages, the applications to disinformation are concerning as the counter-measures …

The recent breakthrough of deep learning based generative models has led to the escalated
generation of photo-realistic synthetic videos with significant visual quality. Automated …

In this paper, we construct CAMU-Net, an image forgery detection method, to obtain
evidence of copy-move forgery areas in images. In CAMU-Net, the hierarchical feature …

Face forgery detection has become a research hotspot due to security concerns about
spreading ultrarealisitc fake faces over social platforms. However, most existing deep …

The serious concerns over the negative impacts of Deepfakes have attracted wide attentions
in the community of multimedia forensics. The existing detection works achieve deepfake …

In this paper, we propose a fine-grained deepfake detection network based on cross-
modality attention. Specifically, it consists of three essential parts. The first is the feature …

The advent of deepfake technology has introduced complex challenges to the information
technology landscape, simultaneously presenting benefits and novel risks and ethical …