Face recognition has been successfully deployed in real-time applications, including secure
applications such as border control. The vulnerability of face recognition systems (FRSs) to …

Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

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 …

Over the past two decades, biometric recognition has exploded into a plethora of different
applications around the globe. This proliferation can be attributed to the high levels of …

Face morphing attacks target to circumvent Face Recognition Systems (FRS) by employing
face images derived from multiple data subjects (eg, accomplices and malicious actors) …

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

Media forensics has attracted a tremendous attention in the last years in part due to the
increasing concerns around DeepFakes. Since the release of the initial DeepFakes …

Deepfakes present an emerging threat in cyberspace. Recent developments in machine
learning make deepfakes highly believable, and very difficult to differentiate between what is …

A robust facial recognition system that has soundness and completeness is essential for
authorized control access to lawful resources. Due to the availability of modern image …

To strengthen the security of face recognition systems to morphing attacks (MAs), many
countermeasures were proposed. However, in the existing face morphing attack detection …