Lidar for Autonomous driving III (Deep Learning)

LiDAR-basedAutonomous Driving III (by Deep Learning)

•CalibNet

•PointPillars

•Complex-YOLO

•Robust Deep Multi-modal Learning Based on GIF Network

•LATTE: Accelerate Lidar Point Cloud Annotation

•FVNet: 3D Front-View Proposal Generation for Object Detection from Point Cloud

•RGB and LiDAR fusion based 3D Semantic Segmentation

•Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds

•STD: Sparse-to-Dense 3D Object Detector for Point Cloud

•End-to-end sensor modeling for LiDAR Point Cloud

•Part-A2 Net

•StarNet: Targeted Computation for Object Detection in Point Clouds

•Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

•Deep Hough Voting for 3D Object Detection in Point Clouds

•MLOD: A multi-view 3D object detection based on robust feature fusion method