awesome-face-recognition
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this repo include paper review, code in face recognition
Awesome Face Recognition
[2020. 02. 02]
- Add Decoupled Network. (in model/dc_module.py)
Implementation
Datasets
- Training
- [x] Faces-emore
- Evaluation
- [x] LFW
- [x] Agedb-30
- [x] CFP-FP
Implemented Networks
- [x] [CVPR 2018] Decoupled Networks
- [x] [CVPR 2019] Arcface
- [x] [CVPR 2019] Regularface
How to train ?
-
Set-up virtual environment.
conda create -n [your environment] python=3.6 source activate [your environment] conda install pytorch cuda90 torchvision -c pytorch pip install -r requirements.txt
-
Download train, test datasets
( https://github.com/TreB1eN/InsightFace_Pytorch —> 3.1 Data Preparation ) -
Training
python train.py --train_root [your data root] --epochs [epochs] --batch_size [batch_size] --save_root [root for saving weights, log file]
Results
- Accuracy : LFW (VGG-19)

- Accuracy : AGE-DB30 (VGG-19)

References
- https://github.com/TreB1eN/InsightFace_Pytorch
- https://github.com/ronghuaiyang/arcface-pytorch
- https://github.com/wy1iu/DCNets