MTCNN_face_detection_alignment

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

Requirement

1. Caffe: Linux OS: https://github.com/BVLC/caffe. Windows OS: https://github.com/BVLC/caffe/tree/windows or https://github.com/happynear/caffe-windows
2. Pdollar toolbox: https://github.com/pdollar/toolbox
3. Matlab 2014b or later
4. Cuda (if use nvidia gpu)

Results

Other implementation

C++ & caffe
Python & mxnet
Python & caffe
Python & Pytorch

Face Recognition

Here we strongly recommend Center Face, which is an effective and efficient open-source tool for face recognition.

Citation

@article{7553523,
    author={K. Zhang and Z. Zhang and Z. Li and Y. Qiao}, 
    journal={IEEE Signal Processing Letters}, 
    title={Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks}, 
    year={2016}, 
    volume={23}, 
    number={10}, 
    pages={1499-1503}, 
    keywords={Benchmark testing;Computer architecture;Convolution;Detectors;Face;Face detection;Training;Cascaded convolutional neural network (CNN);face alignment;face detection}, 
    doi={10.1109/LSP.2016.2603342}, 
    ISSN={1070-9908}, 
    month={Oct}
}
@inproceedings{zhang2017detecting,
    title={Detecting faces using inside cascaded contextual cnn},
    author={Zhang, Kaipeng and Zhang, Zhanpeng and Wang, Hao and Li, Zhifeng and Qiao, Yu and Liu, Wei},
    booktitle={Proceedings of the IEEE International Conference on Computer Vision},
    pages={3171--3179},
    year={2017}
}

License

This code is distributed under MIT LICENSE

Contact

Yu Qiao yu.qiao@siat.ac.cn
Kaipeng Zhang zhangkaipeng@pjlab.org.cn