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Explainable_FIQA_WITH_AMVA


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This is the official repository of the paper: Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models. The paper can be found in here.

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Citation

if you use the data in this repository, please cite the following paper:

@misc{fu2021explainability,
      title={Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models}, 
      author={Biying Fu and Naser Damer},
      year={2021},
      eprint={2112.04827},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

##License This project is licensed under the terms of the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. Copyright (c) 2021 Fraunhofer Institute for Computer Graphics Research IGD Darmstadt.

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Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models

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