… original point cloud directly. It uses Max pooling function to solve the problem that point cloud
… this method gets a better effect compare with our PS structure in point cloud classification. …

… point cloud fusion network (REPF-Net) is designed based on the complementary and enhanced
fusion of … , enhancing the fusion point cloud with RGB feature points, achieving effective …

… present a point cloud panoptic segmentation network utilizing camera-LiDAR sensor fusion.
… In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. …

… - point clouds and optical images fusion algorithm based on depth images. The method maps
the laser-point clouds … , so as to realize the fusion of laser- point clouds and optical images. …

… To this end, we propose a cross-modality feature fusion network to fully employ both raw
point cloud and projected depth image data, and introduce a simple way to fuse features from …

… ), which utilizes pseudo point clouds generated from depth … fusion strategy 3D-GAF (3D
Grid-wise Attentive Fusion) to make fuller use of information from different types of point clouds…

… sensor fusion of camera RGB data and LIDAR point clouds. … point cloud. The two key
technologies of object recognition classification based on multisensor fusion include data fusion …

… visionbased sensors like cameras. However, due to the disorder, sparsity, and irregularity of
the point cloud, … the temporal information in the dynamic 3D point cloud sequences, as it has …

… As such, we argue that a fusion network needs to keep as much point cloud information as
… ,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, …

… Rpvnet: A deep and efficient range-point-voxel fusion network for lidar point cloud
segmentation. ICCV, pages 16004–16013, 2021. 1 [67] Mengde Xu, Zheng Zhang, and etc. …