Over the last few decades, rapid progress in AI, machine learning, and deep learning has
resulted in new techniques and various tools for manipulating multimedia. Though the …

The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …

We propose a new method to detect deepfake images using the cue of the source feature
inconsistency within the forged images. It is based on the hypothesis that images' distinct …

With the rapid development of face manipulation technology, it is difficult for human eyes to
distinguish fake face images. On the contrary, Convolutional Neural Network (CNN) …

The creation or manipulation of facial appearance through deep generative approaches,
known as DeepFake, have achieved significant progress and promoted a wide range of …

A variety of effective face-swap and face-reenactment methods have been publicized in
recent years, democratizing the face synthesis technology to a great extent. Videos …

A light-weight high-performance Deepfake detection method, called DefakeHop, is
proposed in this work. State-of-the-art Deepfake detection methods are built upon deep …

This work introduces a novel DeepFake detection framework based on physiological
measurement. In particular, we consider information related to the heart rate using remote …

Face manipulation techniques develop rapidly and arouse widespread public concerns.
Despite that vanilla convolutional neural networks achieve acceptable performance, they …

Digital face manipulation has become a concern in the last few years due to its harmful
impacts on society. It is especially concerning for high-profile celebrities because their …