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PCN: Point Completion Network

Introduction

PCN

This is implementation of PCN——Point Completion Network in pytorch. PCN is an autoencoder for point cloud completion. As for the details of the paper, please refer to arXiv.

Environment

  • Ubuntu 18.04 LTS
  • Python 3.7.9
  • PyTorch 1.7.0
  • CUDA 10.1.243

Prerequisite

Compile for cd and emd:

cd extensions/chamfer_distance
python setup.py install
cd ../earth_movers_distance
python setup.py install

Hint: Don't compile on Windows platform.

As for other modules, please install by:

pip install -r requirements.txt

Dataset

Please reference render and sample to create your own dataset. Also, we decompressed all .lmdb data from PCN data into .ply data which has smaller volume 8.1G and upload it into Google Drive. Here is the shared link: Google Drive.

Training

In order to train the model, please use script:

python train.py --exp_name PCN_16384 --lr 0.0001 --epochs 400 --batch_size 32 --coarse_loss cd --num_workers 8

If you want to use emd to calculate the distances between coarse point clouds, please use script:

python train.py --exp_name PCN_16384 --lr 0.0001 --epochs 400 --batch_size 32 --coarse_loss emd --num_workers 8

Testing

In order to test the model, please use follow script:

python test.py --exp_name PCN_16384 --ckpt_path <path of pretrained model> --batch_size 32 --num_workers 8

Because of the computation cost for calculating emd for 16384 points, I split out the emd's evaluation. The parameter --emd is used for testing emd. The parameter --novel is for novel testing data contains unseen categories while training. The parameter --save is used for saving the prediction into .ply file and visualize the result into .png image.

Pretrained Model

The pretrained model is in checkpoint/.

Results

I trained the model on Nvidia GPU 1080Ti with L1 Chamfer Distance for 400 epochs with initial learning rate 0.0001 and decay by 0.7 every 50 epochs. The batch size is 32. Best model is the minimum L1 cd one in validation data.

Quantitative Result

The threshold for F-Score is 0.01.

Seen Categories:

Category L1_CD(1e-3) L2_CD(1e-4) EMD(1e-3) F-Score(%)
Airplane 6.0028 1.7323 10.5922 86.2954
Cabinet 11.2092 4.7351 27.1505 61.6697
Car 9.1304 2.7157 14.3661 70.5874
Chair 12.0340 5.8717 22.4904 58.2958
Lamp 12.6754 7.5891 58.7799 57.8894
Sofa 12.8218 6.4572 19.2891 53.4009
Table 9.8840 4.5669 23.7691 70.9750
Vessel 10.1603 4.2766 17.9761 66.6521
Average 10.4897 4.7431 24.3017 65.7207

Unseen Categories

Category L1_CD(1e-3) L2_CD(1e-4) EMD(1e-3) F-Score(%)
Bus 10.5110 4.4648 17.0274 66.9774
Bed 24.9320 32.4809 42.7974 32.2265
Bookshelf 15.8186 13.1783 28.5608 50.0337
Bench 12.1345 7.3033 12.7497 62.4376
Guitar 11.4964 5.9601 28.4223 59.4976
Motorbike 15.3426 8.7723 21.8634 44.7431
Skateboard 13.1909 7.9711 17.9910 58.4427
Pistol 17.4897 15.5062 33.8937 45.6073
Average 15.1145 11.9546 25.4132 52.4958

Qualitative Result

Seen Categories

seen

Unseen Categories

unseen

Citation