… a real-time vehicle detection algorithm which fuses vision and lidar point cloud information.
Firstly, the obstacles are detected by the grid projection method using the lidar point cloud …

… We introduce a novel CNN-based vehicle detector on 3D range data. The proposed model
… of the point cloud and computes for 3D each point its probability of belonging to a vehicle. …

… -time 3D vehicle detection method (RT3D) that utilizes pure LiDAR point cloud to predict the
… In this paper, we present a real-time vehicle detection method RT3D. The pipeline of RT3D …

… HG and HV using only 3D-LIDAR data (to explore how far we can go using a single 3D-LIDAR
point cloud): HG step is achieved by clustering 3D-LIDAR points (after removing ground …

… -point semantic segmentation [6]. To this end, in this work, we will be proposing a DA approach
for vehicle detection in real point cloud … For the vehicle detection task, it will be based on …

… We evaluate our vehicle detection and localization proposal on the challenging KITTI object
detection benchmark [4]. The dataset provides 7,481 images for training with ground truth …

… of the scene by sparse point cloud. In this work, we focus on 3D vehicle detection, whose
goal is to localize the 3D oriented bounding boxes of physical vehicles from the point cloud. By …

… vehicle detection from point clouds … of point clouds and images, feature-level fusion of voxel
and Bird’s Eye View (BEV) in the point cloud branch, and feature-level fusion of point clouds …

… detection, 3D point cloud object detection can provide the three-dimensional information of
the object that the 2D object detection … the original input point cloud and the detection result in …

… the existing vehicle detection methods cannot meet the actual needs. This paper presents
a vehicle detection method combines the intensity and distance information of point cloud, …