This paper reviews the NTIRE 2023 challenge on image denoising (sigma= 50) with a focus
on the proposed solutions and results. The aim is to obtain a network design capable to …

This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images
(restoration of rich details in hazy image). We focus on the proposed solutions and their …

Since convolutional neural networks (CNNs) perform well at learning generalizable image
priors from large-scale data, these models have been extensively applied to image …

In this paper, we present Uformer, an effective and efficient Transformer-based architecture
for image restoration, in which we build a hierarchical encoder-decoder network using the …

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 …

Image restoration tasks demand a complex balance between spatial details and high-level
contextualized information while recovering images. In this paper, we propose a novel …

We investigate the generalization of semi-supervised learning (SSL) to diverse pixel-wise
tasks. Although SSL methods have achieved impressive results in image classification, the …

The availability of large-scale datasets has helped unleash the true potential of deep
convolutional neural networks (CNNs). However, for the single-image denoising problem …

Real-noise denoising is a challenging task because the statistics of real-noise do not follow
the normal distribution, and they are also spatially and temporally changing. In order to cope …

Recently, significant progress has been made on image denoising with strong supervision
from large-scale datasets. However, obtaining well-aligned noisy-clean training image pairs …