In this paper, we analyse the generalization ability of binary classifiers for the task of
deepfake detection. We find that the stumbling block to their generalization is caused by the …

Given the severe vulnerability of Deep Neural Networks (DNNs) against adversarial
examples, there is an urgent need for an effective adversarial attack to identify the …

Recent studies on face forgery detection have shown satisfactory performance for methods
involved in training datasets, but are not ideal enough for unknown domains. This motivates …

Previous studies in deepfake detection have shown promising results when testing face
forgeries from the same dataset as the training. However, the problem remains challenging …

Face forgery detection plays an important role in personal privacy and social security. With
the development of adversarial generative models, high-quality forgery images become …

We propose TextToon, a method to generate a drivable toonified avatar. Given a short
monocular video sequence and a written instruction about the avatar style, our model can …

Deepfakes have rapidly emerged as a profound and serious threat to society, primarily due
to their ease of creation and dissemination. This situation has triggered an accelerated …

Existing face forgery detection methods attempt to identify low-level forgery artifacts (eg,
blending boundary, flickering) in spatial-temporal domains or high-level semantic …

Face authentication usually utilizes deep learning models to verify users with high accuracy.
However, it is vulnerable to various attacks that cheat the models by manipulating the digital …