PCD Anomaly Detection Abstract 名词说明 PCD:Point Cloud DPMF:互补伪多模态特征,就是论文的创新点,即新的点云特征表示(2D+3D) 创新点 提出了新的方法来提取点云特征,具体创新点如下: 通过将手工PCD 描述符与强大的预训练 2D 神经网络相结合来提高 PCD 异常检测性能。 提出了新的提取逐点语义信息的新方法(...
论文代码github.com/llien30/point_cloud_anomaly_detection 论文阅读 个人方法 首先附上个人对于文献阅读的一点理解,用来抛砖引玉: 粗读流程 (1)Abstract 论文提出了一种用于 3D 点云的端到端无监督异常检测框架。 这是第一个针对 3D 点云表示的一般对象处理异常检测任务的工作。 具体来说是一个基于深度变分...
Unlike structured 3D point cloud data, unstructured 3D point cloud data can capture the surface geometry completely. However, anomaly detection by using unstructured 3D point cloud data is more challenging, due to the nonexistence of global coordinate ordering and the difficulty of mathematically ...
Real3D-AD: A Dataset of Point Cloud Anomaly Detection [det; Github; NeurIPS] AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset [pre-training; PyTorch; NeurIPS] Explore In-Context Learning for 3D Point Cloud Understanding [in-context learning; Github; NeurIPS] E2PNet:...
Anomaly Detection: The MVTec 3D-AD dataset already comes in the propoer format to be used with our code. Therefore, it does not need any pre-processing. Unzip it in thedata/folder. Bone Side Estimation: the pre-processing script for the BSE datasets isdata/prepare_bse.pyand can be run...
Fig. 1. Framework of geometric defect detection using deep learning for 3D point cloud analysis. To focus on a tangible problem, this paper primarily investigates the development of deep learning models for defect detection in the context of gear manufacturing. Practical issues related to the metrol...
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Paper tables with annotated results for Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encoder