PyTorch implementation of Seesaw-shuffleFaceNet

Differences from official implementation are minimal:

• Li-ArcFace loss
• Zero γ
• standard SE Block (no bias, no prelu)
• ReLU after first two convolutions
• Hard versions for Swish and Sigmoid

Pretrained model (TorchScript)

Validation metrics can be computed by running python3 eval.py <path to model> <path to a folder containing InsightFace bin files>:

cfp_ff: 99.56%
lfw: 99.62%
agedb_30: 96.12%
vgg2_fp: 93.24%
cfp_fp: 94.49%
cplfw: 89.52%

For training code see foamliu/InsightFace-v3 and similar projects.

Tested with nightly builds of PyTorch (1.4.0.dev20191216).