… , which could not make full use of the advantages of machine vision for obstacle … , which
are called fusion point cloud data in this study. Second, the fusion point data were filtered and …

… With the wide applications of colored point cloud (CPC) in … paper, a Point cloud projection
and Multiscale feature fusion … , then a multi-scale feature fusion network is designed to blindly …

… 3D point cloud … point cloud into 2D BA images and depth images. The RGB image captured
by the camera is used to select the region of interest (ROI) corresponding to the point cloud. …

… segmentation task to identify each point’s semantic label for real point cloud scenes. …
resolution point clouds, and utilize an adaptive fusion method to represent the comprehensive point-…

… based on vision sensors that is suitable for collaborative robotics scenarios. In fact, … in the
form of a point cloud. Two Microsoft Kinect are used and their point cloud data is merged to …

… fusion-based network that takes advantages of mature 2D object detection methods. With
the presence of LiDAR point clouds, … exploits both RGB images and point clouds in the on-road …

… Optical imagery and Light Detection And Ranging (LiDAR) point cloud are two types of major
data sources in the fields of photogrammetry and remote sensing, computer vision, pattern …

… To this end, we first project point clouds to the camera coordinates to provide spatio-depth
information for RGB images. Then, we propose a two-stream network to extract features from …

… for Point cloud understanding with high-frequency encoding, as DSPoint. Specifically, we
disentangle the point … In Proceedings of the IEEE conference on computer vision and pattern …

… of point cloud aims at assigning semantic labels to each point by utilizing … Point-wise LiDAR
and Image Multimodal Fusion Network (PMNet) for 3D segmentation of aerial point cloud by …