Machine learning datasets have elicited concerns about privacy, bias, and unethical
applications, leading to the retraction of prominent datasets such as DukeMTMC, MS-Celeb …

The listening or hearing impaired (deaf/dumb) people use a set of signs, called sign
language instead of speech for communication among them. However, it is very challenging …

The availability of large annotated datasets and affordable computation power have led to
impressive improvements in the performance of convolutional neural networks (CNNs) on …

Face recognition networks encode information about sensitive attributes while being trained
for identity classification. Such encoding has two major issues:(a) it makes the face …

Existing research in the field of face recognition with variations due to disguises focuses
primarily on images captured in controlled settings. Limited research has been performed on …

Face recognition is diversely used in modern biometric and security applications. Most of the
current face recognition techniques show good results in a constrained environment …

Research in face recognition has seen tremendous growth over the past couple of decades.
Beginning from algorithms capable of performing recognition in constrained environments …

As deep networks become increasingly accurate at recognizing faces, it is vital to
understand how these networks process faces. While these networks are solely trained to …

Despite their many advantages and positive features, the deep neural networks are
extremely vulnerable against adversarial attacks. This drawback has substantially reduced …

In the crime scene, criminals often consciously conceal their facial identity through face-
masked disguise, which poses a huge challenge to identity recognition. Existing disguised …