Gluon Face Toolkit

Gluon Face is a toolkit based on MXnet Gluon, provides SOTA deep learning algorithm and models in face recognition. If you are new to mxnet, please check out dmlc 60-minute crash course.


For Chinese readers, here is the zh-doc.

Gluon Face provides implement of losses in recent, including SoftmaxCrossEntropyLoss, ArcLoss, TripletLoss, RingLoss, CosLoss, L2Softmax, ASoftmax, CenterLoss, ContrastiveLoss, … , and we will keep updating in future.


Github: see details in gluon face.

If there is any method we overlooked, please open an issue.

Losses in GluonFR:

The last column of this chart is the best LFW accuracy reported in paper, they are trained with different data and networks, later we will give our results of these method with same train data and network.

Method Paper Visualization of MNIST LFW
Contrastive Loss ContrastiveLoss
Triplet 1503.03832
Center Loss CenterLoss img2 99.28
L2-Softmax 1703.09507
A-Softmax 1704.08063
CosLoss/AMSoftmax 1801.05599/1801.05599 img3 99.17
Arcloss 1801.07698 img4 99.82
Ring loss 1803.00130 img5 99.52
LGM Loss 1803.02988 img6 99.20±0.03


{ haoxintong Yangxv }


中文社区Gluon-Forum Feel free to use English here :D.


  1. MXNet Documentation and Tutorials
  2. NVIDIA DALI documentationNVIDIA DALI documentation
  3. Deepinsight insightface