… We first encode a 3D point cloud to multiple views. Then, we propose a multi-view prompt
vision fusion module based on attention mechanism to exchange and fuse information from …

… We propose a multimodal fusion framework that processes both 3D LIDAR point cloud and
RGB image to obtain robust vehicle position and size in a Bird’s Eye View (BEV). Semantic …

… , the computer vision community as well … fusion of both sensors is reasonable in order to
provide color images with depth and reflectance information as well as 3D LIDAR point clouds …

… vision-language (VL) pre-training methods to 3D vision. … domain, and adapt it to point cloud
classification. We introduce a … aggregators and gated fusion for downstream representative …

… machine vision, the method based on images has been … both sparse visual features and
dense point clouds for frame-to-… The point cloud is registered with 2D and 3D fusion information. …

… 2D computer vision tasks. However, CNNs are unable to process irregular unstructured data
like point clouds directly, how to extract meaningful information from point clouds to analysis …

… point cloud and point cloud of different resolutions. In the case of noise and distortion in the
point cloud… Vision, Seoul, Korea, 27 October–2 November 2019; pp. 12–21. [Google Scholar] …

… , it is mainly due to the fact that this paper presents a view fusion network which can make
full use of the information from multiple views. As can be seen in Table 4, the accuracy drops …

… vision on-vehicle perception systems, LiDAR and camera are usually the two most critical
sensors that provide accurate point cloud … to classify objects on point clouds when LiDAR does …

… The fusion of these modalities increases the dimensionality … In contrast, a 6D-vision approach
[2] computes the 3D scene … for obtaining the low-level fusion of LIDAR and camera data. …