PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)

Implementation of DUL (PyTorch version)

Introduction

This repo is an unofficial PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020).

NOTE:

1. SE-Resnet64 is used as defult backbone in this repo, you can define others in ./backbone/model_irse.py
2. Training (process) & Testing (results) logs are saved in ./exp/logs/ & ./exp/logs_test/
3. Implementation details are not exactly the same as the original paper, seen in ./config.py

Getting Started

• Star this repo, plz

  😊

• Clone this repo

git clone https://github.com/MouxiaoHuang/DUL.git

• Prepare env

conda create --name <env_name> python=3.8
pip install -r requirements.txt

• Prepare trainset and testset
  • Trainset: Casia WebFace or MS-Celeb-1M
  • Testset: LFW, CFP_FF, CFP_FP, AgeDB, CALFW, CPLFW, VGG2_FP
• Training

sh ./exp/Exp_webface_DUL.sh
# or
sh ./exp/Exp_ms1m_DUL.sh

• Testing

sh ./exp/TestFR_webface_DUL.sh
# or
sh ./exp/TestFR_ms1m_DUL.sh

Results Report

• Trainset: Casia Webface

• Trainset: MS-Celeb-1M

Thanks & Refs

• ZhaoJ9014/face.evoLVe
• Ontheway361/dul-pytorch