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 …

Infrared and visible image fusion aims to synthesize a single fused image that not only
contains salient targets and abundant texture details but also facilitates high-level vision …

Underwater image enhancement is such an important low-level vision task with many
applications that numerous algorithms have been proposed in recent years. These …

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 …

Just like many other topics in computer vision, image classification has achieved significant
progress recently by using deep learning neural networks, especially the Convolutional …

We present a comprehensive study and evaluation of existing single image deraining
algorithms, using a new large-scale benchmark consisting of both synthetic and real-world …

In this paper, we conduct a comprehensive study of Underwater Object Detection (UOD).
UOD has evolved into an attractive research field in the computer vision community in recent …

Robust visual recognition under adverse weather conditions is of great importance in real-
world applications. In this context, we propose a new method for learning semantic …

Adverse weather conditions in real-world scenarios lead to performance degradation of
deep learning-based detection models. A well-known method is to use image restoration …

Although considerable progress has been made in semantic scene understanding under
clear weather, it is still a tough problem under adverse weather conditions, such as dense …