An extraordinary challenge for real-world applications is traffic sign recognition, which plays
a crucial role in driver guidance. Traffic signals are very difficult to detect using an extremely …

Underwater images typically suffer from color deviations and low visibility due to the
wavelength-dependent light absorption and scattering. To deal with these degradation …

In this paper, we study a challenging problem in image restoration, namely, how to develop
an all-in-one method that could recover images from a variety of unknown corruption types …

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, we explore the role of Instance Normalization in low-level vision tasks.
Specifically, we present a novel block: Half Instance Normalization Block (HIN Block), to …

Image restoration tasks demand a complex balance between spatial details and high-level
contextualized information while recovering images. In this paper, we propose a novel …

As the computing power of modern hardware is increasing strongly, pre-trained deep
learning models (eg, BERT, GPT-3) learned on large-scale datasets have shown their …

Rain streaks in the air appear in various blurring degrees and resolutions due to different
distances from their positions to the camera. Similar rain patterns are visible in a rain image …

Along with the deraining performance improvement of deep networks, their structures and
learning become more and more complicated and diverse, making it difficult to analyze the …

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 …