Abstract Single Image Super Resolution (SISR) is a process to obtain a high pixel density
and refined details from a low resolution (LR) image to get upscaled and sharper high …

Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual
apps spanning from on-demand movies and 360° videos to video-conferencing and live …

Single image super-resolution (SISR) with generative adversarial networks (GAN) has
recently attracted increasing attention due to its potentials to generate rich details. However …

Structures matter in single image super resolution (SISR). Recent studies benefiting from
generative adversarial network (GAN) have promoted the development of SISR by …

Convolutional neural networks (CNNs) have shown dramatic improvements in single image
super-resolution (SISR) by using large-scale external samples. Despite their remarkable …

Single-image super-resolution (SISR) networks trained with perceptual and adversarial
losses provide high-contrast outputs compared to those of networks trained with distortion …

Efficient and effective real-world image super-resolution (Real-ISR) is a challenging task
due to the unknown complex degradation of real-world images and the limited computation …

This paper presents a new variational inference framework for image restoration and a
convolutional neural network (CNN) structure that can solve the restoration problems …

We consider the single image super-resolution (SISR) problem, where a high-resolution
(HR) image is generated based on a low-resolution (LR) input. Recently, generative …

Usually located at the very early stages of the computational photography pipeline,
demosaicing and denoising play important parts in the modern camera image processing …