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get_dr_py_API

This package is available for using pybind11 to create get_dr python API.

Deformation Representation Feature (DR Feature) is a kind of fundamental and stable tool in geometry learning area. For more background knowledges and properties of DR feature, we suggest these papers in Citation section for further reading.

Dependencies

This package depends on OpenMesh and Eigen libraries. To run the dr computation code, please make sure you have Eigen and OpenMesh precompiled on your computer and modificate the include path in CMakeList.txt file.

Usage

We recommend to use cmake to compile this package and a python API will be automatically created to compute DR features.

git clone --recursive https://github.com/QianyiWu/get_dr_py.git
cd get_dr_py

After obtaining this repository, run the following code in the repository path:

mkdir build
cd build
cmake ..
make -j4

You will then get a .so file. The test.py with 1_new.obj and 2_new.obj could be used for testing.

Environment Tests

Currently we have fully tested this package on Ubuntu 16.04 LTS environment. Windows and MacOS are not ensured working.

Citation

Please cite the following papers if it helps your research:

Disentangled Representation Learning for 3D Face Shape

@inproceedings{Jiang2019Disentangled
      title={Disentangled Representation Learning for 3D Face Shape},
      author={Jiang, Zi-Hang and Wu, Qianyi and Chen, Keyu and Zhang, Juyong}
      booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      year={2019},
}

Sparse Data Driven Mesh Deformation

@article{Gao2017SparseDD,
      title={Sparse Data Driven Mesh Deformation},
      author={Lin Gao and Yu-Kun Lai and Jie Yang and Ling-Xiao Zhang and Leif Kobbelt and Shihong Xia},
      journal={CoRR},
      year={2017},
      volume={abs/1709.01250}
}

Alive Caricature from 2D to 3D

@inproceedings{wu2018alive,
  title={Alive Caricature from 2D to 3D},
  author={Wu, Qianyi and Zhang, Juyong and Lai, Yu-Kun and Zheng, Jianmin and Cai, Jianfei},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2018},
}