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Official repository for MixFaceNets: Extremely Efficient Face Recognition Networks

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This is the official repository of the paper: MixFaceNets: Extremely Efficient Face Recognition Networks.

(Accepted in IJCB2021)https://ieeexplore.ieee.org/abstract/document/9484374

Paper Arxiv

ModelMFLOPsParams (M)LFW%AgeDB-30%IJB-B( TAR at FAR1e–6)IJB-C( TAR at FAR1e–6)Pretrained model
MixFaceNet-M626.13.9599.6897.0591.5593.42pretrained-mode
ShuffleMixFaceNet-M626.13.9599.6096.9891.4793.5pretrained-mode
MixFaceNet-S451.73.0799.6096.6390.1792.30pretrained-mode
ShuffleMixFaceNet-S451.73.0799.5897.0590.9493.08pretrained-mode
MixFaceNet-XS161.91.0499.6095.8588.4890.73pretrained-mode
ShuffleMixFaceNet-XS161.91.0499.5395.6287.8690.43pretrained-mode

FLOPs vs. performance on LFW (accuracy), AgeDB-30 (accuracy), MegaFace (TAR at FAR1e-6), IJB-B (TAR at FAR1e-4), IJB-C (TAR at FAR1e-4) and refined version of MegaFace, noted as MegaFace (R), (TAR at FAR1e-6). Our MixFaceNet models are highlighted with triangle marker and red edge color.

LFWLFW

AgeDb-30LFW

MegaFaceLFW

MegaFace(R)LFW

IJB-BLFW

IJB-CLFW

If you find MixFaceNets useful in your research, please cite the following paper:

Citation

@INPROCEEDINGS{9484374,  author={Boutros, Fadi and Damer, Naser and Fang, Meiling and Kirchbuchner, Florian and Kuijper, Arjan},  booktitle={2021 IEEE International Joint Conference on Biometrics (IJCB)},   title={MixFaceNets: Extremely Efficient Face Recognition Networks},   year={2021},  volume={},  number={},  pages={1-8},  doi={10.1109/IJCB52358.2021.9484374}}

The model is trained with ArcFace loss using Partial-FC algorithms.If you train the MixfaceNets with ArcFace and Partial-FC, please follow their distribution licenses.

Citation

@inproceedings{deng2019arcface,  title={Arcface: Additive angular margin loss for deep face recognition},  author={Deng, Jiankang and Guo, Jia and Xue, Niannan and Zafeiriou, Stefanos},  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},  pages={4690--4699},  year={2019}}@inproceedings{an2020partical_fc,  title={Partial FC: Training 10 Million Identities on a Single Machine},  author={An, Xiang and Zhu, Xuhan and Xiao, Yang and Wu, Lan and Zhang, Ming and Gao, Yuan and Qin, Bin and  Zhang, Debing and Fu Ying},  booktitle={Arxiv 2010.05222},  year={2020}}

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