How Does Gender Balance In Training Data Affect Face Recognition Accuracy?

This repository contains all 42 trained models from the paper How Does Gender Balance In Training Data Affect Face Recognition Accuracy?.

The trained models vary in loss function, training dataset, and gender ratio. It also contains the name of the images used to create the subset from the FRGC dataset.

Models can be downloaded here.

The cleaned Public-IvS that is used in the paper can be found here.

To extract features using the model provided, use insightface_feature_extraction.py.

And to match features, use mult_feature_match_list.py.

You will need a copy of the InsighFace deploy folder.

If you use our model, please cite the paper below.

If you use any of the models or the FRGC subset please cite the paper below.

@misc{albiero2020does,
    title={How Does Gender Balance In Training Data Affect Face Recognition Accuracy?},
    author={Vítor Albiero and Kai Zhang and Kevin W. Bowyer},
    year={2020},
    eprint={2002.02934},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}