Robots and autonomous vehicles can use 3D point clouds from LiDAR sensors and camera images to perform 3D object detection. However, current techniques that combine both types of data struggle to ...

Point-GNN is a machine-learning algorithm that processes the point-cloud data for object detection. Here, we discuss the use of LiDAR data and Point-GNN, as well as modified Resnet, for the detection ...

Ritsumeikan University researchers introduce DPPFA−Net, a groundbreaking 3D object detection network melding LiDAR and image data to improve accuracy for robots and self-driving cars.

LiDAR is one of the vital sensors for perception tasks such as vehicle tracking, drivable region segmentation and object detection. The point cloud created by LiDARs supplies 3D spatial ...

This is according to evaluations run through the KITTI 3D object detection benchmark, which Apple used to assess its process. VoxelNet was trained to detect three basic objects — car, pedestrian ...