模型结构要从算子说起，基于稀疏卷积算子的点云检测模型一直以来是3D PointCloud Detection的重要组成部分,...
通道,点,体素三合一:leveraging channel-wise, point-wise, and voxel-wise attention of point clouds to learn a more discriminative and robust representation for each voxel 第一个注意机制用于3D目标检测:the first one to design the attention mechanism suitable for the 3D object detection task 多层特征...
Use this page to familiarize yourself with the user interface and tools available to complete your 3D point cloud object detection task. Topics Your Task Navigate the UI Icon Guide Shortcuts Release, Stop and Resume, and Decline Tasks Saving Your Work and Submitting Your Task When you work on...
分类(Classification)、部分分割(Part Segmentation)、语义(场景)分割(Semantic Segmentation)、目标检测(Detection)、配准(Registration)等。分类任务顾名思义,根据点云整体形状确定其归属的种类(category),如飞机、椅子等;部分分割则是针对一个点云中的各个点,确定其所属的类别,如飞机可拆分为机身、机翼和机尾三个部分...
论文标题:AGO-Net: Association-Guided 3D Point Cloud Object Detection Network (2022TPAMI) 论文地址:https://arxiv.org/pdf/2208.11658.pdf 作者单位:Liang Du等,复旦大学等 核心思想:作者将现实场景的不完整的稀疏点云定义为感知域,将对应场景补全的完整点...
论文标题:AGO-Net: Association-Guided 3D Point Cloud Object Detection Network (2022TPAMI) 论文地址:https://arxiv.org/pdf/2208.11658.pdf 作者单位:Liang Du等,复旦大学等 核心思想:作者将现实场景的不完整的稀疏点云定义为感知域,将对应场景补全的完整点云定义为概念域,通过孪生网络辅助稀疏点云从完整点云学...
pcl::FPFHEstimation<pcl::PointXYZ, pcl::Normal, pcl::FPFHSignature33> fpfh; fpfh.setInputCloud(cloud); fpfh.setInputNormals(normals); fpfh.setSearchMethod(kdtree); // Search radius, to look for neighbors. Note: the value given here has to be ...
3. PV-RCNN for Point Cloud Object Detection3.1. 3D Voxel CNN for Efficient Feature Encoding and Proposal Generation 3D voxel CNN 3D proposal generation 上面的两点内容大都和其他目前流行的基于voxel的方法一样,不多赘述。 Discussions (1)目前大多精度高的工作都采用了refine优化的工作,这里作者提出两个问...
标题:Learning Transferable Features for Point Cloud Detection via 3D Contrastive Co-training 论文链接:https://proceedings.neurips.cc/paper/2021/file/b3b25a26a0828ea5d48d8f8aa0d6f9af-Paper.pdf 来源:NeurIPS2021 作者:Yihan Zeng , Chunwei Wang, Yunbo Wang, Hang Xu, Chaoqiang Ye, Zhen Yang, Ch...
目标检测(3D Object Detection) 对于检测任务,我们将Point-NN作为一个3D检测器的分类头使用。当预训练好的检测器产生3D proposal后,Point-NN与分类任务相似,使用non-parametric encoder来获取被检测物体的全局特征。在构建point-memory bank时,我们在训练集中对在每个3D框标签内的点云进行采样,将采样后的每个物体的全...