PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition
This addresses robust place recognition for automation systems, particularly in varying conditions like night, but is incremental in combining existing modalities.
The paper tackles place recognition by fusing image and point cloud data using an attention mechanism and day-night image transformation, achieving improved performance over single-modality methods.
Place recognition is one of the hot research fields in automation technology and is still an open issue, Camera and Lidar are two mainstream sensors used in this task, Camera-based methods are easily affected by illumination and season changes, LIDAR cannot get the rich data as the image could , In this paper, we propose the PIC-Net (Point cloud and Image Collaboration Network), which use attention mechanism to fuse the features of image and point cloud, and mine the complementary information between the two. Furthermore, in order to improve the recognition performance at night, we transform the night image into the daytime style. Comparison results show that the collaboration of image and point cloud outperform both image-based and point cloud-based method, the attention strategy and day-night-transform could further improve the performance.