With the rapid development of face forgery techniques, the existing frame-based deepfake
video detection methods have fell into a dilemma that frame-based methods may fail when …

Abstract Face Anti-Spoofing (FAS) is recently studied under the continual learning setting,
where the FAS models are expected to evolve after encountering data from new domains …

Face presentation attacks (FPA), also known as face spoofing, have brought increasing
concerns to the public through various malicious applications, such as financial fraud and …

Nowadays, forgery faces pose pressing security concerns over fake news, fraud,
impersonation, etc. Despite the demonstrated success in intra-domain face forgery …

Face forgery techniques have advanced rapidly and pose serious security threats. Existing
face forgery detection methods try to learn generalizable features, but they still fall short of …

Open-set face forgery detection poses significant security threats and presents substantial
challenges for existing detection models. These detectors primarily have two limitations: they …

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

Face aging tasks aim to simulate changes in the appearance of faces over time. However,
due to the lack of data on different ages under the same identity, existing models are …

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 …

In recent years, deep learning has greatly streamlined the process of generating realistic
fake face images. Aware of the dangers, researchers have developed various tools to spot …