Deep learning techniques have achieved superior performance in computer-aided medical
image analysis, yet they are still vulnerable to imperceptible adversarial attacks, resulting in …

The illegal use of facial forgery models, such as Generative Adversarial Networks (GAN)
synthesized contents, has been on the rise, thereby posing great threats to personal …

Neural style transfer (NST) generates new images by combining the style of one image with
the content of another. However, unauthorized NST can exploit artwork, raising concerns …

The emergence of deep learning has led to the rise of malicious face manipulation
applications, which pose a significant threat to face security. In order to prevent the …

The fast progress of deepfake technology has caused a huge overlap between reality and
deceit, leading to substantial worries over the authenticity of dig-ital media content …

In this work, we propose IDGuard, a novel proactive defense method from the perspective of
developers, to protect Persons-of-Interest (POI) such as national leaders from face editing …

Face-swap models have increasingly gained popularity in recent years because of their
improvement in generation quality and applications in privacy protection and entertainment …

Few-shot image classification (FSIC) is beneficial for a variety of real-world scenarios,
aiming to construct a recognition system with limited training data. In this article, we extend …