deep-face-recognition

State-of-the-art 2D and 3D Face Analysis Project

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931) ECCV Workshops 2022)

Pytorch implementation of Center Loss

This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the same time, this project also supports MelSpectrogram, Spectrogram data preprocessing methods

face recognition algorithms in pytorch framework, including arcface, cosface, sphereface and so on

InsightFace REST API for easy deployment of face recognition services with TensorRT in Docker.

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices

适用于复杂场景的人脸识别身份认证系统