Abstract Generative Adversarial Networks (GAN) have led to the generation of very realistic
face images, which have been used in fake social media accounts and other disinformation …

In this paper, we consider the face swap** detection from the perspective of face identity.
Face swap** aims to replace the target face with the source face and generate the fake …

Deepfake detection remains a challenging task due to the difficulty of generalizing to new
types of forgeries. This problem primarily stems from the overfitting of existing detection …

Existing face forgery detectors mainly focus on specific forgery patterns like noise
characteristics, local textures, or frequency statistics for forgery detection. This causes …

With the springing up of face synthesis techniques, it is prominent in need to develop
powerful face forgery detection methods due to security concerns. Some existing methods …

Deepfake detection faces a critical generalization hurdle with performance deteriorating
when there is a mismatch between the distributions of training and testing data. A broadly …

Misinformation has become a pressing issue. Fake media, in both visual and textual forms,
is widespread on the web. While various deepfake detection and text fake news detection …

In recent years, face forgery detectors have aroused great interest and achieved impressive
performance, but they are still struggling with generalization and robustness. In this work, we …

This paper presents a new approach for the detection of fake videos based on the analysis
of style latent vectors and their abnormal behavior in temporal changes in the generated …

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 …