Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

This work addresses the challenging task of LiDAR-based 3D object detection in foggy
weather. Collecting and annotating data in such a scenario is very time, labor and cost …

Low-light image enhancement is challenging in that it needs to consider not only brightness
recovery but also complex issues like color distortion and noise, which usually hide in the …

In this paper, we study two challenging and less-touched problems in single image
dehazing, namely, how to make deep learning achieve image dehazing without training on …

How to ensure robust and accurate 3D object detection under various environment is
essential for autonomous driving (AD) environment perception. While, until now, most of the …

We address the problem of semantic nighttime image segmentation and improve the state-of-
the-art, by adapting daytime models to nighttime without using nighttime annotations …

With the rapid development of deep learning in recent years, the level of automatic driving
perception has also increased substantially. However, automatic driving perception under …

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 …

Autonomous driving needs to ensure all-weather safety, especially in unfavorable
environments such as night and rain. However, the current daytime-trained semantic …

Hurricanes are among the most devastating natural disasters in the United States, causing
billions of dollars of property damage and insured losses. During extreme wind events …