28 skills found
yanx27 / Pointnet Pointnet2 PytorchPointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
antao97 / PointCloudDatasets3D point cloud datasets in HDF5 format, containing uniformly sampled 2048 points per shape.
jiachens / ModelNet40 CRepo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296
jiawei-ren / ModelNet C[ICML 2022] Benchmarking and Analyzing Point Cloud Classification under Corruptions https://arxiv.org/abs/2202.03377
JulianJuaner / DeepFloorPlan PytorchA PyTorch implementation for the floor plan segmentation on the r2v dataset. As well as a simple 3D mesh modeling script with the ModelNet dataset.
zeaggler / ModelNet Blender OFF2Multiviewfrom ModelNet off file to multiview images
kuixu / 3ddensenet.torch3D DenseNet(torch version) for ModelNet40 dataset
engelnico / Point TransformerThis is the official repository of the original Point Transformer architecture.
hiram64 / 3D Similarity Searchsimilar data search for 3D voxel data
datasets-mila / Datasets Modelnet40No description available
zeaggler / ModelNet OFF2MATYou can easily generate mat files with different views from off file
MingyeXu / Curcatures Estimation On Point CloudsCalculate the curvature of every point in he discrete point cloud and visualize the data from ModelNet40.(http://modelnet.cs.princeton.edu/)
ace19-dev / Mvcnn TfBasic reference for Multi View Classification - mvcnn
fanglaosi / ModelNet O PointMLSImplementation of the paper: ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud Classification
vencia / Multiview RendererBlender rendering script for multi-view images of 3D objects (ModelNet, ShapeNet, ...)
guoguo12 / Modelnet CnnTraining a 3D CNN on the ModelNet10 dataset using Keras.
flatironinstitute / PointCloud RegressionPose regression with new algebraic representation on ModelNet dataset (ICCV 2023)
Y5Whe2D9psemu / Multi View Convolutional Neural Networks For 3D Shape Recognition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，形成一个新的层参与神经网络的训练，以提高卷积神经网络识别多视图的准确率。为了应对数据集较小的情况，我们使用了迁移学习的方法，先使用ModelNET数据集对单视图卷积神经网络进行预训练，然后将预训练模型加载到多视图卷积神经网络后再进行微调，以提高图像的识别率。ModelNET数据集上的实验结果证明了算法的有效性。Keras版本：2.2.4，TensorFlow版本：1.12.0，GPU型号：GeForce RTX 2080 Ti
chiphackers / ModelNetlistThis repository contains a simple model for representing netlist (electronics) in python
cabraile / ModelNet40FixerModelNet40 dataset has errors on it's 'off' files. This repo's application fixes the whole dataset.
