We propose a new deep network architecture for removing rain streaks from individual
images based on the deep convolutional neural network (CNN). Inspired by the deep …

Existing learning-based atmospheric particle-removal approaches such as those used for
rainy and hazy images are designed with strong assumptions regarding spatial frequency …

Rain streaks removal is an important issue in outdoor vision systems and has recently been
investigated extensively. In this paper, we propose a novel video rain streak removal …

Rain removal from a single image is an important issue in the fields of outdoor vision. Rain,
a kind of bad weather that is often seen, usually causes complex local intensity changes in …

Image restoration under severe weather is a challenging task. Most of the past works
focused on removing rain and haze phenomena in images. However, snow is also an …

Recently emerged deep learning methods have achieved great success in single image rain
streaks removal. However, existing methods ignore an essential factor in the rain streaks …

To alleviate the adverse effect of rain streaks in image processing tasks, CNN-based single
image rain removal methods have been recently proposed. However, the performance of …

In rainy conditions, imaging devices often capture degraded and blurry images. Most
existing works on this problem focus on rain streak removal, but these approaches cannot …

Rain removal from a single image is a challenging problem and has attracted much attention
in recent years. In this paper, we revisit the single image deraining problem, and present a …

Existing methods for single images raindrop removal either have poor robustness or suffer
from parameter burdens. In this paper, we propose a new Adjacent Aggregation Network (A …