This paper presents the summary report on our DFGC 2022 competition. The DeepFake is
rapidly evolving, and realistic face-swaps are becoming more deceptive and difficult to …

With the advancement in face manipulation technologies, the importance of face forgery
detection in protecting authentication integrity becomes increasingly evident. Previous …

The illegal use of deepfake technology will have a serious impact on social stability,
personal reputation and even national security. Therefore, it is imperative to develop …

Despite encouraging progress in deepfake detection, generalization to unseen forgery types
remains a significant challenge due to the limited forgery clues explored during training. In …

Hyper-realistic avatars in the metaverse have already raised security concerns about
deepfake techniques, deepfakes involving generated video “recording” may be mistaken for …

Face forgery detection is an important yet challenging task that aims to distinguish whether a
face video has been modified. As various types of face forgery are constantly produced and …

Recent DeepFake detection methods have shown excellent performance on public datasets
but are significantly degraded on new forgeries. Solving this problem is important, as new …

Face forgery technology has developed rapidly, causing severe security issues in society.
Recently, with the continuous emergence of forgery techniques and types, most forensics …

Deepfakes have recently raised significant trust issues and security concerns among the
public. Compared to CNN face forgery detectors, ViT-based methods take advantage of the …

Though existing methods for face forgery detection achieve fairly good performance under
the intra-dataset scenario, few of them gain satisfying results in the case of cross-dataset …