Rain can cause performance degradation of outdoor computer vision tasks. Thus, the
exploration of rain removal from videos or a single image has drawn considerable attention …

Rainy weather is a challenge for many vision-oriented tasks (eg, object detection and
segmentation), which causes performance degradation. Image deraining is an effective …

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

Image deraining has achieved considerable progress based on supervised learning with
synthetic training pairs, but is usually limited in handling real-world rainy images. Although …

This survey article is concerned with the emergence of vision augmentation AI tools for
enhancing the situational awareness of first responders (FRs) in rescue operations. More …

Convolutional neural networks (CNNs) and self-attention (SA) have demonstrated
remarkable success in low-level vision tasks, such as image super-resolution, deraining …

Deep learning models have been able to generate rain-free images effectively, but the
extension of these methods to complex rain conditions where rain streaks show various …

Single image deraining aims to remove rain perturbation while restoring the clean
background scene from a rain image. However, existing methods tend to produce blurry and …

Image restoration in adverse weather conditions is a difficult task in computer vision. In this
paper, we propose a novel transformer-based framework called GridFormer which serves as …

Images captured in low-light or underwater environments are often accompanied by
significant degradation, which can negatively impact the quality and performance of …