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 …

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 …

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 …

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 face restoration usually synthesizes degraded low-quality data with a pre-defined
degradation model for training, while more complex cases could happen in the real world …

As a successful deep model applied in image super-resolution (SR), the Super-Resolution
Convolutional Neural Network (SRCNN)[1, 2] has demonstrated superior performance to the …

This paper is on image and face super-resolution. The vast majority of prior work for this
problem focus on how to increase the resolution of low-resolution images which are …

Abstract Face Super-Resolution (SR) is a domain-specific superresolution problem. The
facial prior knowledge can be leveraged to better super-resolve face images. We present a …

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

Recent reference-based face restoration methods have received considerable attention due
to their great capability in recovering high-frequency details on real low-quality images …