PALF: Pre-Annotation and Camera-LiDAR Late Fusion for the Easy Annotation of Point Clouds

Yucheng Zhang, Masaki Fukuda, Yasunori Ishii, Kyoko Ohshima, Takayoshi Yamashita

Abstract: 3D object detection has become indispensable in the field of autonomous driving. To date, gratifying breakthroughs have been recorded in 3D object detection research, attributed to deep learning. However, deep learning algorithms are data-driven and require large amounts of annotated point cloud data for training and evaluation. Unlike 2D images, annotating point cloud data is difficult due to the limitations of sparsity, irregularity, and low resolution, which requires more manual work, and the annotation efficiency is much lower than annotating 2D images. Therefore, we propose an annotation algorithm for point cloud data, which is pre-annotation and camera-LiDAR late fusion algorithm to annotate easily and accurately.