knut0815 / face_recognition

Face Recognition based on DeepID

Face Recognition based on DeepID

Implementation of DeepID based on the paper "Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes[C]//Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014: 1891-1898."

Dataset preparation

LFW - refer to sklearn.dataset

Facescrub - http://vintage.winklerbros.net/facescrub.html

Cropped only faces, separate them into train, val, and test set with ratio of 0.7, 0.1, 0.2 respectively

Current state

Only done face identification, working on face verification

Training

Initially learning rate of 0.01 using exponential decay on 100000 steps/0.9 decay rate

Monitor the training graph, if it stays at a loss/accuracy for a long time, initialise learning rate with 0.005 or lower (my guess on it, i think it is because it reaches a local minimum gradient, couldn't go deeper)

Reminder

1. Small dataset will be easily overfit as there is nothing much to "learn" from the dataset

2. Due to Internet speed and storage problem, I choose a smaller than CASIA dataset (stated in the paper), but bigger than LFW which is facescrub

3. My code is in continue training state, if you want a new training, comment the "load" code

Performance

Training on LFW - maximum of 80% accuracy (only 68 classes, I choose minimum of 10 faces)

Training on Facescrub - still training, but reached 75% accuracy by the time I commit (530 classes)

Contact

Email: [email protected]

Reference

[1]. https://github.com/RiweiChen/DeepFace

[2]. https://github.com/stdcoutzyx/DeepID_FaceClassify

[3]. Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes[C]//Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014: 1891-1898.