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SelfSupervisedFiseyeRectification

An official pytorch implementation of the paper "Self-Supervised Fisheye Image Rectification by Reconstructing Coordinate Relations"

results.png

Our network is based on single parameter division model, architecture is shown below.

net_arch_full.png

Quick start

  1. Clone the project.

    git clone https://github.com/MasakiHosono/SelfSupervisedFisheyeRectification.git
    
  2. Install the dependencies.

    pip3 install -r requirements.txt
    
  3. Prepare dataset Download cityscapes dataset and put it under data/ in the project root. Then run the following script.

    python3 tools/prepare_cityscapes.py
    
  4. Training.

    python3 src/train.py cfg/cityscapes.yml
    
  5. Testing.

    python3 src/test.py cfg/cityscapes.yml
    

Citation

@inproceedings{hosono2021self,
  title={Self-Supervised Deep Fisheye Image Rectification Approach using Coordinate Relations},
  author={Hosono, Masaki and Simo-Serra, Edgar and Sonoda, Tomonari},
  booktitle={2021 17th International Conference on Machine Vision and Applications (MVA)},
  pages={1--5},
  year={2021},
  organization={IEEE}
}

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An official pytorch implementation of the paper "Self-Supervised Fisheye Image Rectification by Reconstructing Coordinate Relations"

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