With the development of convolutional neural networks, hundreds of deep learning–based
dehazing methods have been proposed. In this article, we provide a comprehensive survey …

Object detection accuracy degrades seriously in visually degraded scenes. A natural
solution is to first enhance the degraded image and then perform object detection. However …

Detecting objects under adverse weather and lighting conditions is crucial for the safe and
continuous operation of an autonomous vehicle, and remains an unsolved problem. We …

Most recently, deep learning-based visual detection has attracted rapidly increasing
attention paid to marine organisms, thereby expecting to significantly benefit ocean ecology …

Single-image haze removal is challenging due to its ill-posed nature. The breadth of real-
world scenarios makes it difficult to find an optimal dehazing approach that works well for …

Haze usually causes severe interference to image visibility. Such degradation on images
troubles both human observers and computer vision systems. To seek high-quality images …

Unpaired image dehazing (UID) holds significant research importance due to the challenges
in acquiring haze/clear image pairs with identical backgrounds. This paper proposes a novel …

Real-world Image Dehazing (RID) aims to alleviate haze-induced degradation in real-world
settings. This task remains challenging due to the complexities in accurately modeling real …

Existing thin cloud removal methods treat this image restoration task as a point estimation
problem, and produce a single cloud-free image following a deterministic pipeline. In this …

Low-resolution ship detection from optical satellite image sequences is critical in high-orbit
remote sensing satellite applications. However, it is still a difficult problem due to the …