… , 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 …

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 …

… 3b compares the mesh reconstructions of NICE-SLAM [79], VoxFusion [69] and our method
… We attribute this to our neural point cloud which adapts the point density where it is needed (…

… 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 …

… 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 …

… 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 …

… two point clouds, which has a unique and critical role in numerous computer vision applications.
The … The point clouds fusion requires cross-source point cloud registration techniques. …

… problem of fusing a lidar point cloud with an RGB image. The point cloud provides a very
accurate … Early work on KITTI [6] such as MV3D [3] and AVOD [10] proposed multi-view fusion …

… Fusion of airborne laserscanning point clouds and images for supervised and unsupervised
scene classification. ISPRS Journal of Photogrammetry and Remote Sensing, 87, 78–92. …