3D Fully Convolutional Network for Vehicle Detection in Point Cloud
This addresses the problem of accurate vehicle detection from lidar data for autonomous driving systems, but it is incremental as it adapts an existing 2D method to 3D.
The paper tackles vehicle detection in 3D point clouds for autonomous driving by extending 2D fully convolutional networks to 3D, resulting in significant performance improvement on the KITTI dataset.
2D fully convolutional network has been recently successfully applied to object detection from images. In this paper, we extend the fully convolutional network based detection techniques to 3D and apply it to point cloud data. The proposed approach is verified on the task of vehicle detection from lidar point cloud for autonomous driving. Experiments on the KITTI dataset shows a significant performance improvement over the previous point cloud based detection approaches.