Awesome GitHub Repositories3D Object Classification

PointNet 是一种深度学习架构，旨在直接处理和分类原始 3D 点云，无需体素化。它提供了一个 3D 对象分类系统、用于将点云划分为类别的语义分割框架，以及可视化 3D 形状的工具。 该项目利用变换网络将点云对齐到规范坐标空间，并采用基于对称函数的聚合方法，无论点序如何，都能将点级特征压缩为全局向量。它还具有多尺度分组架构，用于提取不同空间尺度的层级几何特征。 该系统包含用于将原始 3D 室内解析和形状数据转换为 HDF5 文件以进行训练的数据流水线。评估功能涵盖分割准确度指标，以及将分类错误的 3D 点云渲染为三视图图像以进行误差分析。

PointNet++ is a deep learning framework designed for processing and classifying 3D point cloud data. It utilizes a hierarchical feature learning architecture to extract geometric patterns from sampled 3D point sets. The framework implements a variety of 3D analysis tools, including a point cloud classifier for categorizing objects based on spatial coordinates and surface normals, a semantic scene segmenter for labeling surfaces in large-scale environments, and a tool for 3D object part segmentation. The system covers a broad range of capabilities including geometric feature extraction, 3D da

MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used for tasks such as 3D shape classification or segmentation. This framework includes convolution, pooling and unpooling layers which are applied directly on the mesh edges.

3D Generative Adversarial Network

This repository contains the implementation of our papers related with O-CNN. The code is released under the MIT license.

OctNet uses efficient space partitioning structures (i.e. octrees) to reduce memory and compute requirements of 3D convolutional neural networks, thereby enabling deep learning at high resolutions.

PointConv: Deep Convolutional Networks on 3D Point Clouds. CVPR 2019 Wenxuan Wu, Zhongang Qi, Li Fuxin.

Created by Itai Lang, Asaf Manor, and Shai Avidan from Tel Aviv University.

3D/Volumetric Convolutional Neural Networks with Theano+Lasagne.

Created by Yutong Feng, Yifan Feng, Haoxuan You, Xibin Zhao, Yue Gao from Tsinghua University.

Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation.

Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification

Here you can find the code for the BMVC 2017 version of "Orientation-boosted Voxel Nets for 3D Object Recognition", a.k.a ORION.

Paper: Feedback Networks, CVPR 2017.

SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters. ECCV 2018 Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, Yu Qiao.

1. Python (with necessary common libraries such as numpy, scipy, etc.) 2. TensorFlow 3. You need to prepare your data in *.mat file with the following format: - 'points': N x 3 array (x, y, z coordinates of the point cloud) - 'labels': N x 1 array (1-based integer per-point labels) - 'category':…

Field Probing Neural Networks for 3D Data