Numerous CNN-based algorithms have been proposed to reconstruct high-quality face
images. However, the inability of convolution operation to model long-distance relationships …

To make the face hallucination process robust to impulse noise, a new outlier elimination
based iterative neighbor representation (OEINR) algorithm is proposed in this work. The …

In the Face Super-Resolution (FSR) task, it is important to precisely recover facial textures
while maintaining facial contours for realistic high resolution faces. Although several CNN …

Abstract Generative Adversarial Networks (GANs) have shown an outstanding ability to
generate high-quality images with visual realism and similarity to real images. This paper …

Despite the rapid advancements made with the support of deep learning, Face Super-
Resolution (FSR) methods still suffer from challenges under multiple degradations. These …

Background The utilization of artificial intelligence (AI) in healthcare has significant potential
to revolutionize the delivery of medical services, particularly in the field of telemedicine. In …

Face Super-Resolution (FSR) plays a crucial role in enhancing low-resolution face images,
which is essential for various face-related tasks. However, FSR may alter individuals' …

Deep convolutional neural networks have demonstrated significant performance
improvements in face super-resolution tasks. However, many deep learning-based …

Face restoration (FR) is a specialized field within image restoration that aims to recover low-
quality (LQ) face images into high-quality (HQ) face images. Recent advances in deep …

Whether to use face priors in the face super-resolution (FSR) methods is a symmetry
problem. Various face priors are used to describe the overall and local face features, making …