Transformers-based methods have achieved significant performance in image deraining as
they can model the non-local information which is vital for high-quality image reconstruction …

Recent years have witnessed significant advances in image deraining due to the kinds of
effective image priors and deep learning models. As each deraining approach has …

Image restoration under multiple adverse weather conditions aims to remove weather-
related artifacts by using the single set of network parameters. In this paper, we find that …

Learning-based image deraining methods have made great progress. However, the lack of
large-scale high-quality paired training samples is the main bottleneck to hamper the real …

Convolutional neural network (CNN) and Transformer have achieved great success in
multimedia applications. However, little effort has been made to effectively and efficiently …

Since rain streaks exhibit diverse geometric appearances and irregular overlapped
phenomena, these complex characteristics challenge the design of an effective single image …

Recently, Transformer-based network architectures have achieved significant improvements
over convolutional neural networks (CNNs) in the field of single image deraining, due to the …

How to effectively explore multi-scale representations of rain streaks is important for image
deraining. In contrast to existing Transformer-based methods that depend mostly on single …

Underwater image enhancement presents a significant challenge due to the complex and
diverse underwater environments that result in severe degradation phenomena such as light …

Images have been repeatedly used as the perfect environment to hide information through
the use of steganography techniques. Whether messages, documents or even other images …