Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …

This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on
the participating methods and final results. The challenge addresses the real world setting …

The diversity and complexity of degradations in real-world video super-resolution (VSR)
pose non-trivial challenges in inference and training. First, while long-term propagation …

Single-image super-resolution (SISR) is an important task in image processing, which aims
to enhance the resolution of imaging systems. Recently, SISR has made a huge leap and …

The past few years have seen an accelerating integration of deep learning (DL) techniques
into various remote sensing (RS) applications, highlighting their power to adapt and …

Real-world face super-resolution (SR) is a highly ill-posed image restoration task. The fully-
cycled Cycle-GAN architecture is widely employed to achieve promising performance on …

Unpaired image super-resolution (SR) has recently attracted considerable attention in the
unsupervised SR community. In contrast to supervised SR, existing unpaired SR methods …

Whether conventional machine learning-based or current deep neural networks-based
single image super-resolution (SISR) methods, they are generally trained and validated on …

Recent constellations of optical satellites are adopting multi-image super-resolution (MISR)
from bursts of push-frame images as a way to increase the resolution and reduce the noise …

High-resolution satellite imagery is a key element for many Earth monitoring applications.
Satellites such as Sentinel-2 feature characteristics that are favorable for super-resolution …