Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …

Image super-resolution (SR) is one of the vital image processing methods that improve the
resolution of an image in the field of computer vision. In the last two decades, significant …

Image Super-Resolution (SR) is an important class of image processing techniqueso
enhance the resolution of images and videos in computer vision. Recent years have …

General image super-resolution techniques have difficulties in recovering detailed face
structures when applying to low resolution face images. Recent deep learning based …

For all the ways convolutional neural nets have revolutionized computer vision in recent
years, one important aspect has received surprisingly little attention: the effect of image size …

Face image super resolution (face hallucination) usually relies on facial priors to restore
realistic details and preserve identity information. Recent advances can achieve impressive …

Face super-resolution (FSR), also known as face hallucination, which is aimed at enhancing
the resolution of low-resolution (LR) face images to generate high-resolution face images, is …

Recent works based on deep learning and facial priors have succeeded in super-resolving
severely degraded facial images. However, the prior knowledge is not fully exploited in …

Face restoration is important in face image processing, and has been widely studied in
recent years. However, previous works often fail to generate plausible high quality (HQ) …

Recently, deep convolution neural networks (CNNs) steered face super-resolution methods
have achieved great progress in restoring degraded facial details by joint training with facial …