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 …

Blind face restoration usually relies on facial priors, such as facial geometry prior or
reference prior, to restore realistic and faithful details. However, very low-quality inputs …

Blind face restoration (BFR) from severely degraded face images in the wild is a very
challenging problem. Due to the high illness of the problem and the complex unknown …

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 …

Blind image super-resolution (SR), aiming to super-resolve low-resolution images with
unknown degradation, has attracted increasing attention due to its significance in promoting …

In most existing learning systems, images are typically viewed as 2D pixel arrays. However,
in another paradigm gaining popularity, a 2D image is represented as an implicit neural …

Face super-resolution (FSR) aims to reconstruct high-resolution (HR) face images from the
low-resolution (LR) ones. With the advent of deep learning, the FSR technique has achieved …

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

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