The automotive domain is highly regulated, with many safety-critical aspects to consider.
This means that a great deal of testing is required to validate the performance of automotive …

Adverse weather conditions degrade the quality of images used in vision-based advanced
driver assistance systems (ADAS) and autonomous driving algorithms. Adherent raindrops …

Research on the effect of adverse weather conditions on the performance of vision-based
algorithms for automotive tasks has had significant interest. It is generally accepted that …

The presence of raindrop induced distortion can have a significant negative impact on
computer vision applications. Here we address the problem of visual raindrop distortion in …

Lane segmentation and Lane Keeping Assist System (LKAS) play a vital role in autonomous
driving. While deep learning technology has significantly improved the accuracy of lane …

Autonomous vehicles use cameras as one of the primary sources of information about the
environment. Adverse weather conditions such as raindrops, snow, mud, and others, can …

Rain produces a complex set of visual effects on an image captured by a camera sensor.
Hence, the performance of any vision-based system gets adversely affected due to rain …

The raindrops on the glass will affect driving safety, such as rear-view camera, outside mirror
and windshield, etc. This article proposed a robust raindrop detection using deep learning …

We present an implementation of a rain simulation and rain removal framework, which is
based on video streams captured with a stereo camera system. This framework can be used …

Vision-based Driver Assistance Systems (DAS) are becoming pervasive in today's
automotive industry. However, most of these systems are designed to perform in good …