Astounding results from Transformer models on natural language tasks have intrigued the
vision community to study their application to computer vision problems. Among their salient …

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 …

Given a degraded input image, image restoration aims to recover the missing high-quality
image content. Numerous applications demand effective image restoration, eg …

With the goal of recovering high-quality image content from its degraded version, image
restoration enjoys numerous applications, such as in surveillance, computational …

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 …

For medical image analysis, there is always an immense need for rich details in an image.
Typically, the diagnosis will be served best if the fine details in the image are retained and …

Recent advances in image super-resolution (SR) explored the power of deep learning to
achieve a better reconstruction performance. However, the feedback mechanism, which …

This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in
conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at …

Recent research on super-resolution has achieved greatsuccess due to the development of
deep convolutional neu-ral networks (DCNNs). However, super-resolution of arbi-trary scale …

Due to the significant information loss in low-resolution (LR) images, it has become
extremely challenging to further advance the state-of-the-art of single image super …