Arbitrary-scale super-resolution via deep learning: A comprehensive survey
Super-resolution (SR) is an essential class of low-level vision tasks, which aims to improve
the resolution of images or videos in computer vision. In recent years, significant progress …
the resolution of images or videos in computer vision. In recent years, significant progress …
A review on Single Image Super Resolution techniques using generative adversarial network
K Singla, R Pandey, U Ghanekar - Optik, 2022 - Elsevier
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 …
and refined details from a low resolution (LR) image to get upscaled and sharper high …
Srdiff: Single image super-resolution with diffusion probabilistic models
H Li, Y Yang, M Chang, S Chen, H Feng, Z Xu, Q Li… - Neurocomputing, 2022 - Elsevier
Single image super-resolution (SISR) aims to reconstruct high-resolution (HR) images from
given low-resolution (LR) images. It is an ill-posed problem because one LR image …
given low-resolution (LR) images. It is an ill-posed problem because one LR image …
Srflow: Learning the super-resolution space with normalizing flow
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 …
low-resolution image. This fundamental fact is largely ignored by state-of-the-art deep …
Dear-gan: Degradation-aware face restoration with gan prior
With the development of generative adversarial networks (GANs), recent face restoration
(FR) methods often utilize pre-trained GAN models (ie,, StyleGAN2) as prior to generate rich …
(FR) methods often utilize pre-trained GAN models (ie,, StyleGAN2) as prior to generate rich …
NTIRE 2022 challenge on learning the super-resolution space
This paper reviews the NTIRE 2022 challenge on learning the super-Resolution space. This
challenge aims to raise awareness that the super-resolution problem is ill-posed. Since …
challenge aims to raise awareness that the super-resolution problem is ill-posed. Since …
NTIRE 2021 learning the super-resolution space challenge
This paper reviews the NTIRE 2021 challenge on learning the super-Resolution space. It
focuses on the participating methods and final results. The challenge addresses the problem …
focuses on the participating methods and final results. The challenge addresses the problem …
NTIRE 2022 image inpainting challenge: Report
Image Inpainting has recently become an important research problem due to the rise of
generative image synthesis models. While many solutions have been proposed for this …
generative image synthesis models. While many solutions have been proposed for this …
Variational autoencoder for reference based image super-resolution
In this paper, we propose a novel reference based image super-resolution approach via
Variational AutoEncoder. Existing state-of-the-art methods mainly focus on single image …
Variational AutoEncoder. Existing state-of-the-art methods mainly focus on single image …
Text-guided Explorable Image Super-resolution
In this paper we introduce the problem of zero-shot text-guided exploration of the solutions
to open-domain image super-resolution. Our goal is to allow users to explore diverse …
to open-domain image super-resolution. Our goal is to allow users to explore diverse …