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