Over the past years, deep learning capabilities and the availability of large-scale training
datasets advanced rapidly, leading to breakthroughs in face recognition accuracy. However …

Advancements in deep learning techniques and the availability of free, large databases
have made it possible, even for non-technical people, to either manipulate or generate …

Recently, researchers found that the intended generalizability of (deep) face recognition
systems increases their vulnerability against attacks. In particular, the attacks based on …

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 …

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

The vulnerability of facial recognition systems to face morphing attacks is well known. Many
different approaches for morphing attack detection (MAD) have been proposed in the …

Recent research found that attacks based on morphed face images, ie, morphing attacks,
pose a severe security risk to face recognition systems. A reliable morphing attack detection …

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 morphing attack proved to be a serious threat for modern automated border control
systems where face recognition is used to link the identity of a passenger to his/her e …

Face morphing attacks aim at creating face images that are verifiable to be the face of
multiple identities, which can lead to building faulty identity links in operations like border …