Verification with ArcFace pretrained model: https://github.com/deepinsight/insightface
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face_det.py: using MTCNN to extract faces and align
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extract_feature.py: extract 512 (or 128)-dim vector of faces
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verification.py: find the best threshold
Put pretrained models follow below structure:
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models\mobilefacenet\json and params file
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models\resnet34
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models\resnet50
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models\resnet100
Download CASIA_FACE_V5
mkdir aligned_faces, faces_pose, features, scores directory
CASIA FACE V5
http://www.idealtest.org/dbDetailForUser.do?id=9
ARCFACE
@inproceedings{deng2019retinaface,
title={RetinaFace: Single-stage Dense Face Localisation in the Wild},
author={Deng, Jiankang and Guo, Jia and Yuxiang, Zhou and Jinke Yu and Irene Kotsia and Zafeiriou, Stefanos},
booktitle={arxiv},
year={2019}
}
@inproceedings{guo2018stacked,
title={Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment},
author={Guo, Jia and Deng, Jiankang and Xue, Niannan and Zafeiriou, Stefanos},
booktitle={BMVC},
year={2018}
}
@article{deng2018menpo,
title={The Menpo benchmark for multi-pose 2D and 3D facial landmark localisation and tracking},
author={Deng, Jiankang and Roussos, Anastasios and Chrysos, Grigorios and Ververas, Evangelos and Kotsia, Irene and Shen, Jie and Zafeiriou, Stefanos},
journal={IJCV},
year={2018}
}
@inproceedings{deng2018arcface,
title={ArcFace: Additive Angular Margin Loss for Deep Face Recognition},
author={Deng, Jiankang and Guo, Jia and Niannan, Xue and Zafeiriou, Stefanos},
booktitle={CVPR},
year={2019}
}