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pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

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PointNet.pytorch

This repo is implementation for PointNet(https://arxiv.org/abs/1612.00593) in pytorch. The model is in pointnet/model.py.

It is tested with pytorch-1.0.

Download data and running

git clone https://github.com/fxia22/pointnet.pytorch
cd pointnet.pytorch
pip install -e .

Download and build visualization tool

cd script
bash build.sh #build C++ code for visualization
bash download.sh #download dataset

Training

cd utils
python train_classification.py --dataset <dataset path> --nepoch=<number epochs> --dataset_type <modelnet40 | shapenet>
python train_segmentation.py --dataset <dataset path> --nepoch=<number epochs> 

Use --feature_transform to use feature transform.

Performance

Classification performance

On ModelNet40:

Overall Acc
Original implementation 89.2
this implementation(w/o feature transform) 86.4
this implementation(w/ feature transform) 87.0

On A subset of shapenet

Overall Acc
Original implementation N/A
this implementation(w/o feature transform) 98.1
this implementation(w/ feature transform) 97.7

Segmentation performance

Segmentation on A subset of shapenet.

Class(mIOU) Airplane Bag Cap Car Chair Earphone Guitar Knife Lamp Laptop Motorbike Mug Pistol Rocket Skateboard Table
Original implementation 83.4 78.7 82.5 74.9 89.6 73.0 91.5 85.9 80.8 95.3 65.2 93.0 81.2 57.9 72.8 80.6
this implementation(w/o feature transform) 73.5 71.3 64.3 61.1 87.2 69.5 86.1 81.6 77.4 92.7 41.3 86.5 78.2 41.2 61.0 81.1
this implementation(w/ feature transform) 87.6 81.0

Note that this implementation trains each class separately, so classes with fewer data will have slightly lower performance than reference implementation.

Sample segmentation result: seg

Links

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About

pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

License:MIT License


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