Moving Object Detection (MOD) is a critical vision task for successfully achieving safe
autonomous driving. Despite plausible results of deep learning methods, most existing …

Enhancing the accuracy and reliability of perception systems in automated vehicles is
critical, especially under varying driving conditions. Unfortunately, the challenges of adverse …

DAVIS camera, streaming two complementary sensing modalities of asynchronous events
and frames, has gradually been used to address major object detection challenges (eg, fast …

Event cameras with their high temporal and dynamic range and minimal memory usage
have found applications in various fields. However their potential in static traffic monitoring …

Low-light video enhancement (LLVE) is an important yet challenging task with many
applications such as photographing and autonomous driving. Unlike single image low-light …

Event-based cameras are devices based on neuromorphic sensors that are gaining
popularity in different fields, including robotics. They are suitable for tasks where high …

Event-based cameras are predestined for Intelligent Transportation Systems (ITS). They
provide very high temporal resolution and dynamic range, which can eliminate motion blur …

The development process of high fidelity SLAM systems depends on their validation upon
reliable datasets. Towards this goal, we propose IBISCape, a simulated benchmark that …

Sensor fusion is a crucial augmentation technique for improving the accuracy and reliability
of perception sys-tems for automated vehicles under diverse driving conditions. However …

In this paper we delve into the nuanced challenge of tailoring the Segment Anything Models
(SAMs) for integration with event data with the overarching objective of attaining robust and …