In autonomous driving, 3D vehicle detection plays an important role in traffic safety, and the
detection of occluded vehicles is equally important. Different from 2D images, the point …

Thanks to the major advancements in hardware and computational power, sensor
technology, and artificial intelligence, the race for fully autonomous driving systems is …

3-D vehicle detection is a key perception technique in autonomous driving. In this article, a
novel 3-D vehicle detection framework that fuses camera images and Light Detection and …

A fast lidar-camera fusion method is proposed to detect road in autonomous vehicles. The
height data of lidar is transformed to spherical coordinate system to increase the data …

This paper presents a real-time approach to detect and localize surrounding vehicles in
urban driving scenes. We propose a multimodal fusion framework that processes both 3D …

In autonomous driving, 3D object detection based on multi-modal data has become an
indispensable perceptual approach when facing complex environments around the vehicle …

This paper presents Multi-view Labelling Object Detector (MLOD). The detector takes an
RGB image and a LIDAR point cloud as input and follows the two-stage object detection …

In the field of autonomous driving, 3D object detection is a very important perception
module. Although the current SOTA algorithm combines Camera and Lidar sensors, limited …

Autonomous vehicles are equipped with complimentary sensors to perceive the
environment accurately. Deep learning models have proven to be the most effective …

Autonomous driving relies heavily on the vehicle's ability to perceive and understand its
environment accurately. Among various sensors, LIDAR (Light Detection and Ranging) …