Image deblurring is a classic problem in low-level computer vision with the aim to recover a
sharp image from a blurred input image. Advances in deep learning have led to significant …

3D face reconstruction algorithms from images and videos are applied to many fields, from
plastic surgery to the entertainment sector, thanks to their advantageous features. However …

The advancement in the computational capability and storage size of a modern mobile
device has evolved it into a multi-purpose smart device for individual and business needs …

Cybersecurity in front of attacks to a face recognition system is an emerging issue in the
cloud era, especially due to its strong bonds with the privacy of the users registered to the …

With the unprecedented success of deep learning in computer vision tasks, many cloud-
based visual analysis applications are powered by deep learning models. However, the …

Current face recognition tasks are usually carried out on high-quality face images, but in
reality, most face images are captured under unconstrained or poor conditions, eg, by video …

Cameras usually produce low-quality images under low-light conditions. Though many
methods have been proposed to enhance the visibility of low-light images, they are mainly …

Realistic low-resolution (LR) face images refer to those captured by the real-world
surveillance cameras at extreme standoff distances, thereby LR and poor in quality …

Gait recognition is a promising biometric method that aims to identify pedestrians from their
unique walking patterns. Silhouette modality, renowned for its easy acquisition, simple …

Image resolution, or in general, image quality, plays an essential role in the performance of
today's face recognition systems. To address this problem, we propose a novel combination …