PointNet is a deep learning architecture designed to process 3D point clouds directly. This implementation demonstrates: Note: The dataset is approximately 4.8GB and is not included in this repository ...
How can the dense point clouds that originate from 3D mapping be turned into useful game engine scenes? This article considers issues including point classification and segmentation, geometric ...
Abstract: 3D point cloud is an important geometric data structure. In recent years, deep learning for 3D point cloud has attracted more and more attention and has been widely applied in autonomous ...
Department of Civil and Environmental Engineering, National Center for Airborne Laser Mapping (NCALM), University of Houston, Houston, TX, United States The study explores deep learning to perform ...
Read this guide to the main 3D data representation methods to understand the key differences and choose the best method for your specific applications. The 3D data jungle in today’s computerized ...
Several computer vision tasks require perceiving or interacting with 3D environments and objects therein, making a strong case in favor of 3D deep learning. However, unlike images which are most ...
Abstract: Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention, but ignore ...
MN10_Our_Model.ipynb Voxel-based model on ModelNet10, without orientation MN10_PointNet.ipynb PointNet model on ModelNet10, without orientation MN40_our_model.ipynb Voxel-based model on ModelNet40, ...
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