Fusion of Camera and LiDAR for Autonomous Vehicles I (via Deep Learning)
•A General Pipeline for 3D Detection of Vehicles
•Combining LiDAR Space Clustering and Convolutional Neural Networks for Pedestrian Detection
•Fusing Bird’s Eye View LIDAR Point Cloud and Front View Camera Image for Deep Object Detection
•PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
•RoarNet: A Robust 3D Object Detection based on RegiOn Approximation Refinement
•Joint 3D Proposal Generation and Object Detection from View Aggregation
•Frustum PointNets for 3D Object Detection from RGB-D Data
•Deep Continuous Fusion for Multi-Sensor 3D Object Detection
•Multi-View 3D Object Detection Network for Autonomous Driving
•End-to-end Learning of Multi-sensor 3D Tracking by Detection