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Pei-KaiHuang / ICIP23_D-LDCformer

ICIP'23 Incorporating Learnable Descriptive Convolution to Vision Transformer for Face Anti-Spoofing
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LDCformer

LDCformer: Incorporating Learnable Descriptive Convolution to Vision Transformer for Face Anti-Spoofing (ICIP '23)

Decoupled Learnable Descriptive Convolution (Decoupled-LDC)

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Architecture of LDCformer

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Architecture of Decoupled-LDC Block

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Requirements

numpy==1.23.3
pytz==2022.4
requests==2.28.1
scikit_learn==1.2.0
timm==0.6.7
torch==1.10.1
torchvision==0.11.2

Training & Testing

Run train.py to train LDCformer

Run test.py to test LDCformer

Citation

If you use the LDCformer/Decoupled-LDC, please cite the paper:

@inproceedings{huang2023ldcformer,
  title={LDCformer: Incorporating Learnable Descriptive Convolution to Vision Transformer for Face Anti-Spoofing},
  author={Huang, Pei-Kai and Chiang, Cheng-Hsuan and Chong, Jun-Xiong and Chen, Tzu-Hsien and Ni, Hui-Yu and Hsu, Chiou-Ting},
  booktitle={2023 IEEE International Conference on Image Processing (ICIP)},
  pages={121--125},
  year={2023},
  organization={IEEE}
}
 @inproceedings{huang2022learnable,
  title={Learnable Descriptive Convolutional Network for Face Anti-Spoofing},
  author={Huang, Pei-Kai and H.Y. Ni and Y.Q. Ni and C.T. Hsu},
  booktitle={BMVC},
  year={2022}
}