• D-DPCC
• Reference
• Requirements
• Train and Test
• • Train D-DPCC models:
  • Train lossless model for the compression of 2x downsampled coordinates:
  • Test:
  • Probable problems in testing:
• Results

D-DPCC

This is the code of D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion Prediction.

Link of the paper: https://www.ijcai.org/proceedings/2022/0126.pdf

Reference

If you want to cite our work, please use the following reference:

@inproceedings{ijcai2022p126,
title = {D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion Prediction},
author = {Fan, Tingyu and Gao, Linyao and Xu, Yiling and Li, Zhu and Wang, Dong},
booktitle = {Proceedings of the Thirty-First International Joint Conference on
Artificial Intelligence, {IJCAI-22}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Lud De Raedt},
pages = {898--904},
year = {2022},
month = {7},
note = {Main Track},
doi = {10.24963/ijcai.2022/126},
url = {https://doi.org/10.24963/ijcai.2022/126},
}

Requirements

(Also shown in requirements.txt)

cuda~=11.5.50

numpy~=1.21.2

open3d~=0.14.1

pandas~=1.2.3

torch~=1.10.0

MinkowskiEngine~=0.5.4

pytorch3d~=0.6.1

tqdm~=4.62.3

tensorboardX~=2.5

matplotlib~=3.5.1

h5py~=3.6.0

torchac~=0.9.3

setuptools~=58.0.4

scipy~=1.7.3

scikit-learn~=1.0.2

Train and Test

Train D-DPCC models:

python trainer.py --batch_size=4 --gpu=0 --lamb=10 --exp_name=I10 --dataset_dir='/tmp/dataset/8iVFB'

Train lossless model for the compression of 2x downsampled coordinates:

python trainer_lossless.py --dataset_dir='/home/zhaoxudong/dataset_npy'

In fact, the pretrained model is lossless_coder.pth. You probably needn't to retrain this model.

Test:

Estimate the bitrate with factorized entropy model, without practical and separate encoding and decoding process:

# python test_owlii.py --log_name='aaa' --gpu=1 --frame_count=32 --results_dir='results' --tmp_dir='tmp' --dataset_dir='/home/zhaoxudong/Owlii_10bit'
python test_owlii.py --log_name='aaa' --gpu=0 --frame_count=32 --results_dir='results' --tmp_dir='tmp' --dataset_dir='/tmp/dataset/8iVFB'

With separate encoding and decoding process, which generates real bitstream,
and calculate encoding and decoding time.

python test_time.py --log_name='aaa' --gpu=0 --frame_count=32 --results_dir='results' --tmp_dir='tmp' --dataset_dir='/tmp/dataset/8iVFB'

Probable problems in testing:

• If ./GPCC/tmc3: Permission denied:

chmod 777 ./GPCC/tmc3

• If ./GPCC/pc_error: Permission denied:

chmod 777 ./GPCC/pc_error

• The folder PCGCv2 need to be copied and in both the parent and current directory.

Results

Shown in the folder results_csv.

See details in the MPEG proposal: M60267 “[AI-3DGC] D-DPCC Test Results on 10 bit Owlii”, 2022/7.