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
GitHub https://github.com/ZhaoJ9014/face.evoLVe.PyTorch

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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I apply innovative technologies like machine learning, computer vision, and physics to further an organization's goals. Am recognized innovator with 66 patents.