17 مستودعات
Awesome GitHub Repositories3D Object Classification
Neural network architectures for recognizing and categorizing 3D shapes.
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Awesome 3D Object Classification GitHub Repositories
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- charlesq34/pointnet
charlesq34/pointnet
5,433عرض على GitHubPointNet هو بنية تعلم عميق مصممة لمعالجة وتصنيف سحب النقاط ثلاثية الأبعاد الخام مباشرة دون الحاجة إلى تحويلها إلى فوكسل (voxelization). يوفر نظاماً لتصنيف الكائنات ثلاثية الأبعاد، وأطر عمل للتقسيم الدلالي (semantic segmentation) لتقسيم السحب إلى فئات، وأدوات لتصور الأشكال ثلاثية الأبعاد. يستخدم المشروع شبكة تحويل لمحاذاة سحب النقاط في مساحة إحداثيات قانونية، ويستخدم تجميعاً قائماً على الدوال المتماثلة لتكثيف الميزات النقطية في متجهات عالمية بغض النظر عن ترتيب النقاط. كما يتميز ببنية تجميع متعددة المقاييس لاستخراج ميزات هندسية هرمية عبر مقاييس مكانية مختلفة. يتضمن النظام خطوط أنابيب بيانات لتحويل بيانات تحليل الأشكال والأماكن المغلقة ثلاثية الأبعاد الخام إلى ملفات HDF5 للتدريب. تغطي قدرات التقييم مقاييس دقة التقسيم وعرض سحب النقاط ثلاثية الأبعاد المصنفة بشكل خاطئ في صور ثلاثية الزوايا لتحليل الأخطاء.
Deep learning on point sets for classification and segmentation.
Python - charlesq34/pointnet2
charlesq34/pointnet2
3,678عرض على GitHubPointNet++ 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
Deep hierarchical feature learning on point sets.
Python - ranahanocka/meshcnn
ranahanocka/MeshCNN
1,727عرض على GitHubMeshCNN 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.
Neural network for processing 3D triangular meshes.
Python - zck119/3dgan-release
zck119/3dgan-release
3D Generative Adversarial Network
Probabilistic latent space modeling for 3D shapes.
Python - microsoft/o-cnn
Microsoft/O-CNN
This repository contains the implementation of our papers related with O-CNN. The code is released under the MIT license.
Octree-based convolutional neural networks for shape analysis.
C++ - griegler/octnet
griegler/octnet
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.
Octree-based deep 3D representation learning.
C++ - dylanwusee/pointconv
DylanWusee/pointconv
PointConv: Deep Convolutional Networks on 3D Point Clouds. CVPR 2019 Wenxuan Wu, Zhongang Qi, Li Fuxin.
Convolutional operator for point cloud processing.
Python - itailang/samplenet
itailang/SampleNet
Created by Itai Lang, Asaf Manor, and Shai Avidan from Tel Aviv University.
Differentiable point cloud sampling for deep learning.
Python - dimatura/voxnet
dimatura/voxnet
3D/Volumetric Convolutional Neural Networks with Theano+Lasagne.
3D convolutional neural network for real-time object recognition.
Python - yue-group/meshnet
Yue-Group/MeshNet
Created by Yutong Feng, Yifan Feng, Haoxuan You, Xibin Zhao, Yue Gao from Tsinghua University.
Mesh-based neural network for shape representation.
Python - charlesq34/3dcnn.torch
charlesq34/3dcnn.torch
Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation.
Volumetric and multi-view CNNs for 3D object classification.
Lua - ajbrock/generative-and-discriminative-voxel-modeling
ajbrock/Generative-and-Discriminative-Voxel-Modeling
Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification
Generative and discriminative voxel modeling with CNNs.
Python - lmb-freiburg/orion
lmb-freiburg/orion
Here you can find the code for the BMVC 2017 version of "Orientation-boosted Voxel Nets for 3D Object Recognition", a.k.a ORION.
Orientation-boosted voxel nets for object recognition.
Matlab - amir32002/feedback-networks
amir32002/feedback-networks
Paper: Feedback Networks, CVPR 2017.
Feedback-based neural network architecture.
Lua - xyf513/spidercnn
xyf513/SpiderCNN
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters. ECCV 2018 Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, Yu Qiao.
Neural network architecture for point cloud classification.
Python - trucleduc/pointgrid
trucleduc/PointGrid
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':…
Deep network for 3D shape understanding.
Python - yangyanli/fpnn
yangyanli/FPNN
Field Probing Neural Networks for 3D Data
Field probing neural networks for 3D data.
C++
