Ntire 2024 challenge on image super-resolution (x4): Methods and results
This paper reviews the NTIRE 2024 challenge on image super-resolution (x4) highlighting
the solutions proposed and the outcomes obtained. The challenge involves generating …
the solutions proposed and the outcomes obtained. The challenge involves generating …
Dual aggregation transformer for image super-resolution
Transformer has recently gained considerable popularity in low-level vision tasks, including
image super-resolution (SR). These networks utilize self-attention along different …
image super-resolution (SR). These networks utilize self-attention along different …
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 …
N-gram in swin transformers for efficient lightweight image super-resolution
While some studies have proven that Swin Transformer (Swin) with window self-attention
(WSA) is suitable for single image super-resolution (SR), the plain WSA ignores the broad …
(WSA) is suitable for single image super-resolution (SR), the plain WSA ignores the broad …
Masked image training for generalizable deep image denoising
When capturing and storing images, devices inevitably introduce noise. Reducing this noise
is a critical task called image denoising. Deep learning has become the de facto method for …
is a critical task called image denoising. Deep learning has become the de facto method for …
Rethinking alignment in video super-resolution transformers
The alignment of adjacent frames is considered an essential operation in video super-
resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are …
resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are …
Feature modulation transformer: Cross-refinement of global representation via high-frequency prior for image super-resolution
Transformer-based methods have exhibited remarkable potential in single image super-
resolution (SISR) by effectively extracting long-range dependencies. However, most of the …
resolution (SISR) by effectively extracting long-range dependencies. However, most of the …
ESSAformer: Efficient transformer for hyperspectral image super-resolution
Single hyperspectral image super-resolution (single-HSI-SR) aims to restore a high-
resolution hyperspectral image from a low-resolution observation. However, the prevailing …
resolution hyperspectral image from a low-resolution observation. However, the prevailing …
Rethinking multi-contrast mri super-resolution: Rectangle-window cross-attention transformer and arbitrary-scale upsampling
Recently, several methods have explored the potential of multi-contrast magnetic resonance
imaging (MRI) super-resolution (SR) and obtain results superior to single-contrast SR …
imaging (MRI) super-resolution (SR) and obtain results superior to single-contrast SR …
Crafting training degradation distribution for the accuracy-generalization trade-off in real-world super-resolution
Super-resolution (SR) techniques designed for real-world applications commonly encounter
two primary challenges: generalization performance and restoration accuracy. We …
two primary challenges: generalization performance and restoration accuracy. We …