In the literature, several 3D face datasets have been collected, aiming at advancing the field
of 3D face analysis from different perspectives. Data collection generally follows specific …

As violent criminals, such as child sex offenders, tend to have high recidivism rates in
modern society, there is a need to prevent such offenders from approaching socially …

Existing face datasets often lack sufficient representation of occluding objects, which can
hinder recognition, but also supply meaningful information to understand the visual context …

The majority of recent face recognition systems are based on Deep Convolutional Neural
Networks (DCNNs). These networks are trained on massive amounts of face images so as to …

Adversarial attacks on deep learning-based models pose a significant threat to the current AI
infrastructure. Among them, Trojan attacks are the hardest to defend against. In this paper …

Effectiveness of deep learning-based face recognition systems often relies on having a
substantial number of annotated training samples per identity. The addition of new identities …

The human face can appear different depending on the circumstances because of its
flexibility and three-dimensional structure. Researchers are facing several obstacles relating …

In many real-world problems, there is typically a large discrepancy between the
characteristics of data used in training versus deployment. A prime example is the analysis …

Among different biometric modalities, face is becoming a hot research topic due to its
distinctive advantages, such as non-intrusive, friendliness, contact-less, and convenience …

The post COVID world has completely disrupted our lifestyle, where wearing a mask is
necessary to protect ourselves and others from contracting the virus. However, face masks …