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 …

This paper reviews the first challenge on single image super-resolution (restoration of rich
details in an low resolution image) with focus on proposed solutions and results. A new …

Diffusion models have demonstrated impressive performance in various image generation,
editing, enhancement and translation tasks. In particular, the pre-trained text-to-image stable …

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

Both non-local (NL) operation and sparse representation are crucial for Single Image Super-
Resolution (SISR). In this paper, we investigate their combinations and propose a novel Non …

Informative features play a crucial role in the single image super-resolution task. Channel
attention has been demonstrated to be effective for preserving information-rich features in …

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

Learning-based single image super-resolution (SISR) methods are continuously showing
superior effectiveness and efficiency over traditional model-based methods, largely due to …

Super-resolution is an ill-posed problem, since it allows for multiple predictions for a given
low-resolution image. This fundamental fact is largely ignored by state-of-the-art deep …

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 …