Face.evoLVe: Face Recognition Library (align, detect, augment, ResNet, DenseNet, MobileNet, etc.)
Face.evoLVe: Face Recognition Library (align, detect, augment, ResNet, DenseNet, MobileNet, etc.)
Face.evoLVe: A High-Performance Face Recognition Library
arXiv paper abstract https://arxiv.org/abs/2107.08621v1
arXiv PDF paper https://arxiv.org/pdf/2107.08621v1.pdf
We develop a comprehensive library, namely face.evoLVe, for face-related analytics and applications,
including face alignment (e.g., detection, landmark localization, affine transformation, etc.),
data processing (e.g., augmentation, data balancing, normalization, etc.), where
various backbones (e.g., ResNet, IR, IR-SE, ResNeXt, SE-ResNeXt, DenseNet, LightCNN, MobileNet, ShuffleNet , DPN, etc.) with
alternating losses (e.g., Softmax, Focal, Center, SphereFace, CosFace, AmSoftmax, ArcFace, Triplet, etc.) and
bags of tricks (e.g., training refinements, model tweaks, knowledge distillation, etc.) for improving performance have been
provided in standard implementations.
... supports multi-GPU training on top of different deep learning platforms, such as PyTorch and PaddlePaddle
... Note that we have used face.evoLVe to participate in a number of face recognition competitions and secured the first place. ...
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