This paper reviews the NTIRE 2023 challenge on image super-resolution (x4), focusing on
the proposed solutions and results. The task of image super-resolution (SR) is to generate a …

Recently, Transformer-based models are taken much focus on solving the task of image
super-resolution (SR) due to their ability to achieve better performance. However, these …

Recently, vision transformers have demonstrated their superiority against convolutional
neural networks (ConvNet) in various tasks including single-image super-resolution (SISR) …

In single-image super-resolution (SISR) tasks, many methods benefit from the local and
global contexts of the image. Despite that, no methods use the bidirectional interaction …

The single image super-resolution (SISR) task much consideration in the last few years.
There are many image SR models that are developed based on advanced deep learning …

The single image super-resolution (SISR) task has received much attention due to the wide
range of applications in many tasks. The progress in this SISR is mainly based on deep …

Abstract Medical Image Super-Resolution plays a pivotal role in enhancing diagnostic
accuracy. Transformer-based methods, such as Image Restoration Using Swin Transformer …

Generative adversarial networks (GAN) and generative diffusion models (DM) have been
widely used in real-world image super-resolution (Real-ISR) to enhance the image …

Attention mechanisms have been introduced to exploit deep-level information for image
restoration by capturing feature dependencies. However, existing attention mechanisms …

The single image super-resolution (SISR) is a computer vision task needed in many real-
world applications. There are many methods developed to solve ill-posed SISR problem; …