The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …

In recent years, researchers have proposed many deep learning (DL) methods for various
tasks, and particularly face recognition (FR) made an enormous leap using these …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

Heterogeneous faces are acquired with different sensors, which are closer to real-world
scenarios and play an important role in the biometric security field. However, heterogeneous …

Heterogeneous face recognition (HFR) is a challenging problem in face recognition and
subject to large textural and spatial structure differences of face images. Different from …

Composite face sketch recognition is a challenging problem in face recognition, which is
important for law enforcement. Considering composite sketch is generated from facial …

Due to the great texture discrepancies between photos and sketches, matching face
sketches against mug shot photos is a challenging yet important topic in face recognition …

Face sketch to digital image matching is an important challenge of face recognition that
involves matching across different domains. Current research efforts have primarily focused …

Matching facial sketches to digital face images has widespread application in law
enforcement scenarios. Recent advancements in technology have led to the availability of …

Face sketches are able to capture the spatial topology of a face while lacking some facial
attributes such as race, skin, or hair color. Existing sketch-photo recognition approaches …