… Combined with the fusion calibration result, the point cloud data acquired by the 3D laser …
the point cloud data obtained by the above two sensors to obtain a complete point cloud model …

… -local-based feature fusion method to fuse two frames of point cloud. The proposed method
… In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt …

… in the emerging domain of LiDAR point cloud is still an open … In this paper, we present a
fast and robust LiDAR point cloud … -view fusion for 3d object detection in lidar point clouds. In …

… two fusion methods to combine RGB image and point cloud data. … point cloud data or
fusing image features with point cloud … Vision and Pattern Recognition, pp. 4404–4413 (2020) …

… , we proposed a new deep learning framework which fuses LIDAR point cloud into the region
proposal generation process. We name the framework as PC-CNN, in which PC stands for …

… semantic segmentation holds a significant position in computer vision due to its real-time
perception, analysis, and elaboration of an interpretation of dynamic scenes, which leads to …

With the dramatic growth of 3D shape data, 3D shape recognition has become a hot research
topic in the field of computer vision. How to effectively utilize the multimodal characteristics …

… Although 3D object detection methods based on feature fusion have … point clouds. In this
paper, we propose a new feature fusion-based method, which can generate virtual point cloud …

… fusion (APCF), to adaptively capture scales of contextual information from a multiscale feature
pyramid for the point cloud. … an active research topic in 3-D computer vision, especially for …

… tool for LiDAR point clouds. LATTE features the following innovations: 1) Sensor fusion: We
… labels to the point cloud. 2) One-click annotation: Instead of drawing 3D bounding boxes or …