Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …

This study aims to comprehensively review and empirically evaluate the application of
multimodal large language models (MLLMs) and Large Vision Models (VLMs) in object …

Every year, the number of vehicles on the road will be increasing. as claimed by a road
transport department (JPJ) data in Malaysia, there were around 31.2 million units of motor …

Pedestrian detection is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …

Snow is one of the toughest adverse weather conditions for object detection (OD). Currently,
not only there is a lack of snowy OD datasets to train cutting-edge detectors, but also these …

Deep learning models are increasingly used in mobile applications as critical components.
Unlike the program bytecode whose vulnerabilities and threats have been widely-discussed …

Large-scale synthetic traffic image datasets have been widely used to make compensate for
the insufficient data in real world. However, the mismatch in domain distribution between …

Vehicle detection is an indispensable part of environmental perception technology for smart
cars. Aiming at the issues that conventional vehicle detection can be easily restricted by …

Most successful object detectors are anchor-based, which is difficult to adapt to the diversity
of traffic objects. In this paper, we propose a novel anchor-free method, called FII-CenterNet …

Road accidents and traffic congestion are two critical problems for global transport systems.
Connected vehicles (CV) and automated vehicles (AV) are among the most heavily …