Transformer has recently gained considerable popularity in low-level vis...
Super-resolution (SR) techniques designed for real-world applications
co...
Deep deraining networks, while successful in laboratory benchmarks,
cons...
Diffusion models (DMs) have recently been introduced in image deblurring...
When capturing and storing images, devices inevitably introduce noise.
R...
In this paper, we present a hybrid X-shaped vision Transformer, named
Xf...
Transformer architectures have exhibited remarkable performance in image...
The recurrent structure is a prevalent framework for the task of video
s...
Recently, Transformer architecture has been introduced into image restor...
Event cameras are novel bio-inspired vision sensors that output pixel-le...
The attention mechanism plays a pivotal role in designing advanced
super...
Rendering high-resolution (HR) graphics brings substantial computational...
Recently, Transformer-based image restoration networks have achieved
pro...
The alignment of adjacent frames is considered an essential operation in...
This paper reports on the NTIRE 2022 challenge on perceptual image quali...
Performance and generalization ability are two important aspects to eval...
Recent advances in single image super-resolution (SISR) have achieved
ex...
Dropout is designed to relieve the overfitting problem in high-level vis...
Blind image super-resolution (SR), aiming to super-resolve low-resolutio...
Convolutional neural networks have allowed remarkable advances in single...
Image quality assessment (IQA) is the key factor for the fast developmen...
Image super-resolution (SR) techniques have been developing rapidly,
ben...
This paper reviews the video extreme super-resolution challenge associat...
Image quality assessment (IQA) is the key factor for the fast developmen...
Despite the success of Generative Adversarial Networks (GANs) in image
s...
Despite the recent advance of Generative Adversarial Networks (GANs) in
...
Large deep networks have demonstrated competitive performance in single ...
Demosaicing, denoising and super-resolution (SR) are of practical import...
Deep learning based methods have dominated super-resolution (SR) field d...
Generating plausible hair image given limited guidance, such as sparse
s...
The Super-Resolution Generative Adversarial Network (SRGAN) is a seminal...
Image of a scene captured through a piece of transparent and reflective
...