Vision transformers have been demonstrated to yield state-of-the-art results on a variety of
computer vision tasks using attention-based networks. However, research works in …

Automatic detection and classification of traffic signs have become an essential asset in the
visual system of autonomous vehicles and self-driving cars. Recently, vision transformers …

Autonomous vehicles rely on perceiving the road environment through a perception pipeline
fed by a variety of sensor modalities, including camera, lidar, radar, infrared, gated camera …

Autonomous driving is a safety-critical application that requires a high-level understanding
of computer vision with real-time inference. In this study, we focus on the computational …

Visual perception is a critical task for autonomous driving. Understanding the driving
environment in real time can assist a vehicle in driving safely. In this study, we proposed a …

The panoptic driving perception system stands as a pivotal element in autonomous driving,
encapsulating the detection of traffic objects, the segmentation of drivable areas, and the …

The active scene flow estimation technology aims at higher quality of scene flow data
through actively changing the ego-vehicle's trajectory as well as sensor observation …

To tackle the challenges posed by dense small objects and fuzzy boundaries on
unstructured roads in the mining scenario, we proposed an end-to-end small object …

In autonomous driving, environmental perception technology often encounters challenges
such as false positives, missed detections, and low accuracy, particularly in detecting small …

Freespace detection is one of the key technologies for scene understanding and motion
planning in autonomous vehicles. However, current research on freespace detection …