3D Mask-Based Shape Loss Function for LIDAR Data for Improved 3D Object Detection

In this paper, we propose a 3D shape loss function for improved 3D object detection for LIDAR data. As the LiDAR (Light Detection And Ranging) sensor plays a key role in many autonomous driving techniques, 3D object detection using LiDAR data has become an important issue. Due to inaccurate height estimation, 3D object detection methods using LiDAR data produce false positive errors. We propose a new 3D shape loss function based on 3D masks for improved performance. To accurately estimate ground ROI areas, we first apply an adaptive ground ROI estimation method to accurately estimate ground ROIs and then use the shape loss function to reduce false positive errors. Experimental shows some promising results.