HI, the repo is a nice work, thanks for your sharing.
I want to know if these augmentation methods are effective,
like the RandomErasing/Mixup/RandAugment/Cutout/CutMix?
Implementation of related angular-margin-based classification loss functions for training (face) embedding models: SphereFace, CosFace, ArcFace and MagFace.
Face Recognition training and testing framework with tensorflow 2.0 based on the well implemented arcface-tf2. Changes are added to provide tensorflow lite conversion, and provide additional backbones, loss functions.
HI, the repo is a nice work, thanks for your sharing.
I want to know if these augmentation methods are effective,
like the RandomErasing/Mixup/RandAugment/Cutout/CutMix?