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

Overview

Explainable_FIQA_WITH_AMVA


Note

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.

Pipeline Overview

overview

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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