The revolution in computer hardware, especially in graphics processing units and tensor
processing units, has enabled significant advances in computer graphics and artificial …

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 recognition has evolved as a widely used biometric modality. However, its vulnerability
against presentation attacks poses a significant security threat. Though presentation attack …

Object detection models perform well at localizing and classifying objects that they are
shown during training. However, due to the difficulty and cost associated with creating and …

We propose a novel approach to achieving invariance for deep neural networks in the form
of inducing amnesia to unwanted factors of data through a new adversarial forgetting …

Presentation attacks are recurrent threats to biometric systems, where impostors attempt to
bypass these systems. Humans often use background information as contextual cues for …

Vulnerability against presentation attacks remains a challenging issue limiting the reliable
use of face recognition systems. Though several methods have been proposed in the …

Presentation attack detection (PAD) is now considered critically important for any face-
recognition (FR) based access-control system. Current deep-learning based PAD systems …

In this work, we present a general framework for building a biometrics system capable of
capturing multispectral data from a series of sensors synchronized with active illumination …

Supervised machine learning models often associate irrelevant nuisance factors with the
prediction target, which hurts generalization. We propose a framework for training robust …