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DENse and Diverse symmetry dataset (DENDI), CVPR 2022

<p align="center"> Ahyun Seo, Byungjin Kim, Suha Kwak, Minsu Cho </p> <p align="center"> <a href="https://arxiv.org/abs/2203.16787">[paper]</a> <a href="http://cvlab.postech.ac.kr/research/EquiSym">[project page (EquiSym)]</a> </p>

Official Dataset proposed in Reflection and Rotation Symmetry Detection via Equivariant Learning (CVPR 2022).

Contributors of this dataset: Ahyun Seo, Byungjin Kim, Yunseon Choi

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Environment

    conda create --name DENDI python=3.7
    conda activate DENDI
    conda install pytorch==1.7.0 torchvision==0.8.1 -c pytorch
    conda install -c conda-forge matplotlib
    pip install albumentations==0.5.2 shapely opencv-python
    
    mkdir sym_datasets

Datasets

.
├── sym_datasets
│   └── DENDI
│       ├── symmetry
│       ├── symmetry_polygon
│       ├── reflection_split.pt
│       ├── rotation_split.pt
│       └── joint_split.pt
└── (...)

Citation

If you find our code or paper useful to your research work, please consider citing:

@inproceedings{seo2022dendi,
    author   = {Seo, Ahyun and Kim, Byungjin and Kwak, Suha and Cho, Minsu},
    title    = {Reflection and Rotation Symmetry Detection via Equivariant Learning},
    booktitle= {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year     = {2022}
}