Perception and Sensing for Autonomous Vehicles Under Adverse Weather Conditions: A Survey [PDF]
Isprs Journal of Photogrammetry and Remote Sensing, 2021 Automated Driving Systems (ADS) open up a new domain for the automotive industry and offer new possibilities for future transportation with higher efficiency and comfortable experiences.
Yuxiao Zhang +3 more
openalex +3 more sources
Weather Conditions, Weather Information and Car Crashes [PDF]
ISPRS International Journal of Geo-Information, 2015 Road traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts.
Adriaan Perrels +3 more
doaj +3 more sources
Background segmentation in difficult weather conditions [PDF]
PeerJ Computer Science, 2022 Background segmentation is a process in which an algorithm removes the static background from an image. This allows only a changing section of the image. This process is important for motion detection or object tracking.
Lukasz Karbowiak, Janusz Bobulski
doaj +4 more sources
CrackNet-Weather: An Effective Pavement Crack Detection Method Under Adverse Weather Conditions [PDF]
SensorsAccurate pavement crack detection under adverse weather conditions is essential for road safety and effective pavement maintenance. However, factors such as reduced visibility, background noise, and irregular crack morphology make this task particularly ...
Wei Wang +8 more
doaj +2 more sources
Restoring Vision in Adverse Weather Conditions With Patch-Based Denoising Diffusion Models [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Image restoration under adverse weather conditions has been of significant interest for various computer vision applications. Recent successful methods rely on the current progress in deep neural network architectural designs (e.g., with vision ...
Ozan Özdenizci, R. Legenstein
semanticscholar +1 more source
TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions [PDF]
Computer Vision and Pattern Recognition, 2021 Removing adverse weather conditions like rain, fog, and snow from images is an important problem in many applications. Most methods proposed in the literature have been designed to deal with just removing one type of degradation.
Jeya Maria Jose Valanarasu +2 more
semanticscholar +1 more source
Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions [PDF]
AAAI Conference on Artificial Intelligence, 2021 Though deep learning-based object detection methods have achieved promising results on the conventional datasets, it is still challenging to locate objects from the low-quality images captured in adverse weather conditions.
Wenyu Liu +5 more
semanticscholar +1 more source
GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions [PDF]
International Journal of Computer Vision, 2023 Image restoration in adverse weather conditions is a difficult task in computer vision. In this paper, we propose a novel transformer-based framework called GridFormer which serves as a backbone for image restoration under adverse weather conditions ...
Tao Wang +8 more
semanticscholar +1 more source
Survey on LiDAR Perception in Adverse Weather Conditions [PDF]
2023 IEEE Intelligent Vehicles Symposium (IV), 2023 Autonomous vehicles rely on a variety of sensors to gather information about their surrounding. The vehicle’s behavior is planned based on the environment perception, making its reliability crucial for safety reasons.
M. Dreissig +3 more
semanticscholar +1 more source
SemOD: Semantic-Enabled Object Detection Network Under Various Weather Conditions. [PDF]
Sensors (Basel)Zuo A, Zheng Z.
europepmc +2 more sources