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 …

Abstract Single Image D eraining (SID) aims at recovering the rain-free background from an
image degraded by rain streaks. For the powerful fitting ability of deep neural networks and …

Existing deep learning based de-raining approaches have resorted to the convolutional
architectures. However, the intrinsic limitations of convolution, including local receptive fields …

In this paper, an ill-posed problem of multiple adverse weather removal is investigated. Our
goal is to train a model with a'unified'architecture and only one set of pretrained weights that …

Deep learning (DL) methods have achieved state-of-the-art performance in the task of single
image rain removal. Most of current DL architectures, however, are still lack of sufficient …

Removing rain streaks from a single image has been drawing considerable attention as rain
streaks can severely degrade the image quality and affect the performance of existing …

Single image rain streak removal is an extremely challenging problem due to the presence
of non-uniform rain densities in images. We present a novel density-aware multi-stream …

Severe weather conditions, such as rain and snow, adversely affect the visual quality of
images captured under such conditions, thus rendering them useless for further usage and …

Single image rain removal is a typical inverse problem in computer vision. The deep
learning technique has been verified to be effective for this task and achieved state-of-the-art …

Most deraining works focus on rain streaks removal but they cannot deal adequately with
heavy rain images. In heavy rain, streaks are strongly visible, dense rain accumulation or …