FPVT--Face Pyramid Vision Transformer

Usage Instructions

1. Preparation

Please install all dependencies pip3 install -r requirement.txt

pip3 install vit-pytorch

torch==1.8.1
torchvision==0.9.0+cu111
matplotlib==3.3.4
numpy==1.20.3
mxnet==1.8.0.post0
sklearn==0.0
scikit-learn==0.24.2
bcolz==1.2.1
pillow==8.2.0
ipython==7.22.0
scipy==1.6.3
opencv-python==4.5.1.48
tensorboardx==2.2
timm==0.3.2
ptflops==0.6.5
pyyaml==5.4.1
einops==0.3.0
pandas==1.3.1

2. Databases

You can download the training databases, faceScrub cleaned (version FaceScrub), and put it in folder 'Data'.

You can download the testing databases as follows and put them in folder 'eval'.

• LFW: Baidu Netdisk(password: dfj0)
• SLLFW: Baidu Netdisk(password: l1z6)
• CALFW: Baidu Netdisk(password: vvqe)
• CPLFW: Baidu Netdisk(password: jyp9)
• TALFW: Baidu Netdisk(password: izrg)
• CFP_FP: Baidu Netdisk(password: 4fem)--refer to Insightface
• AGEDB: Baidu Netdisk(password: rlqf)--refer to Insightface

Citation

If you find this code useful for your research, please cite our work

@InProceedings{Khawar_BMVC22_FPVT,
      author = {Khawar Islam, Muhammad Zaigham Zaheer, Arif Mahmood},
      title = {Face Pyramid Vision Transformer},
      booktitle = {Proceedings of the British Machine Vision Conference},
      year = {2022}
}
@inproceedings{islam2021face,
      title={Face Recognition Using Shallow Age-Invariant Data},
      author={Islam, Khawar and Lee, Sujin and Han, Dongil and Moon, Hyeonjoon},
      booktitle={2021 36th International Conference on Image and Vision Computing New Zealand (IVCNZ)},
      pages={1--6},
      year={2021},
      organization={IEEE}
}

Contact

If you find any problem in code and want to ask any question, please send us email khawarr dot islam at gmail dot com

Acknowledgment

The code is mainly adopted from Face Transformer, Vision Transformer, and DeiT.