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README

Cycle4Completion

This repository contains the source code for the paper Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding. Intro pic

Cite this work

@inproceedings{wen2021c4c,
  title={Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding},
  author={Wen, Xin and Han, Zhizhong and Cao, Yan-Pei and Wan, Pengfei and Zheng, Wen and Liu, Yu-Shen},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021}
}

Datasets

Preprocessed 3D-EPN dataset can be downloaded from: https://drive.google.com/file/d/1TxM8ZhaKEZWWSnakU2KGBLAO0pRnKDKo/view?usp=sharing

Requirements

Python 2.7 Tensorflow 1.14.0 For detailed implementation, please follow PointNet++ on this page: https://github.com/charlesq34/pointnet2

Getting Started

  1. Unzip the downloaded dataset file "dataset.rar" to the "dataset" folder.

  2. To train Cycle4Completion, you can simply use the following command:

python main.py

License

This project is open sourced under MIT license.

Core symbols most depended-on inside this repo

log_string
called by 10
main_code.py
dtype
called by 9
externals/python_plyfile/plyfile.py
_lookup_type
called by 8
externals/python_plyfile/plyfile.py
write
called by 8
externals/python_plyfile/plyfile.py
mlp_conv
called by 5
utils/net_util.py
describe
called by 4
externals/python_plyfile/plyfile.py
dtype
called by 4
externals/python_plyfile/plyfile.py
list_dtype
called by 4
externals/python_plyfile/plyfile.py

Shape

Method 89
Function 68
Class 16

Languages

Python77%
C++23%

Modules by API surface

externals/python_plyfile/plyfile.py77 symbols
externals/structural_losses/tf_approxmatch.cpp21 symbols
utils/io_util.py16 symbols
utils/net_util.py14 symbols
externals/structural_losses/tf_nndistance.cpp13 symbols
utils/data_provider.py7 symbols
main_code.py7 symbols
externals/structural_losses/approxmatch.cpp6 symbols
externals/structural_losses/tf_approxmatch.py5 symbols
model_code.py3 symbols
externals/structural_losses/tf_nndistance.py3 symbols
externals/structural_losses/tf_hausdorff_distance.py1 symbols

For agents

$ claude mcp add Cycle4Completion \
  -- python -m otcore.mcp_server <graph>

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