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 …

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 …

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 …

Learning single image deraining (SID) networks from an unpaired set of clean and rainy
images is practical and valuable as acquiring paired real-world data is almost infeasible …

In the real world, image degradations caused by rain often exhibit a combination of rain
streaks and raindrops, thereby increasing the challenges of recovering the underlying clean …

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 …

Existing rain-removal algorithms often tackle either rain streak removal or raindrop removal,
and thus may fail to handle real-world rainy scenes. Besides, the lack of real-world deraining …

Single image deraining is important for many high-level computer vision tasks since the rain
streaks can severely degrade the visibility of images, thereby affecting the recognition and …

Single Image Deraining (SID) is a relatively new and still challenging topic in emerging
vision applications, and most of the recently emerged deraining methods use the supervised …

Inpainting arbitrary missing regions is challenging because learning valid features for
various masked regions is nontrivial. Though U-shaped encoder-decoder frameworks have …