PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
翻译 - PointNet 和 PointNet++ 由 pytorch（纯 python）在 ModelNet、ShapeNet 和 S3DIS 上实现。
Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296
from ModelNet off file to multiview images
This repository contains a simple model for representing netlist (electronics) in python
Training a 3D CNN on the ModelNet10 dataset using Keras.
[ICML 2022] Benchmarking and Analyzing Point Cloud Classification under Corruptions https://arxiv.org/abs/2202.03377
3D point cloud datasets in HDF5 format, containing uniformly sampled 2048 points per shape.
You can easily generate mat files with different views from off file
3D DenseNet(torch version) for ModelNet40 dataset
本文提出了一种基于多视图卷积神经网络的三维物体识别算法，以实现三维物体的准确识别。首先实现一个标准的卷积神经网络架构，该架构经过训练可以独立地识别形状的渲染视图，以实现即使从单一视图中也可以识别出一个三维形状。随后使用该三维物体多个角度的二维视图通过卷积神经网络识别的结果进行模型融合。在模型融合的过程中取出输入单角度视图的卷积神经网络的某一层，使用层最大值算法将多个层中同一位置的最大值取出，形成一...