This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …

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 …

Deep learning based approaches has achieved great performance in single image super-
resolution (SISR). However, recent advances in efficient super-resolution focus on reducing …

Recent advances in single image super-resolution (SISR) have achieved extraordinary
performance, but the computational cost is too heavy to apply in edge devices. To alleviate …

Blind face restoration usually relies on facial priors, such as facial geometry prior or
reference prior, to restore realistic and faithful details. However, very low-quality inputs …

Transformer has recently gained considerable popularity in low-level vision tasks, including
image super-resolution (SR). These networks utilize self-attention along different …

Deep convolutional neural networks can effectively improve the performance of single-
image super-resolution reconstruction. Deep networks tend to achieve better performance …

Recent advances in single image super-resolution (SISR) explored the power of
convolutional neural network (CNN) to achieve a better performance. Despite the great …

To improve the issue of low-frequency and high-frequency components from feature maps
being treated equally in existing image super-resolution reconstruction methods, the paper …

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 …