## Cite Kornia papers
  1. Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
  2. A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
  3. Differentiable Data Augmentation with Kornia
  4. torchgeometry: when PyTorch meets geometry
  ```bash
  @inproceedings{eriba2019kornia,
    author    = {E. Riba, D. Mishkin, D. Ponsa, E. Rublee and G. Bradski},
    title     = {Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
    booktitle = {Winter Conference on Applications of Computer Vision},
    year      = {2020},
    url       = {https://arxiv.org/pdf/1910.02190.pdf}
  }
  ```
  ```bash
  @misc{riba2020survey,
      title={A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
      author={E. Riba and D. Mishkin and J. Shi and D. Ponsa and F. Moreno-Noguer and G. Bradski},
      year={2020},
      eprint={2009.10521},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
  }
  ```
  ```bash
  @misc{shi2020differentiable,
      title={Differentiable Data Augmentation with Kornia},
      author={Jian Shi and Edgar Riba and Dmytro Mishkin and Francesc Moreno and Anguelos Nicolaou},
      year={2020},
      eprint={2011.09832},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
  }
  ```
  ```bash
  @misc{Arraiy2018,
    author    = {E. Riba, M. Fathollahi, W. Chaney, E. Rublee and G. Bradski},
    title     = {torchgeometry: when PyTorch meets geometry},
    booktitle = {PyTorch Developer Conference},
    year      = {2018},
    url       = {https://drive.google.com/file/d/1xiao1Xj9WzjJ08YY_nYwsthE-wxfyfhG/view?usp=sharing}
  }
  ```