Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data

Related tags

Deep LearningFTL_net
Overview

FTLNet_Pytorch

Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data


1. Introduction

  • This repo is an unofficial implementation of Feature Transfer Learning for Face Recognition with Under-Represented Data (paper)

2. Build/Run docker environment

  • Please build up docker environment and do everything in it.
  cd ./docker/
  ./build.sh
  • When docker build is done, run docker to enter docker shell by
  cd ./docker/
  ./run.sh

3. Prepare Train and Verification Datasets

  • download the refined emore dataset from InsightFace_Pytorch

  • after unzip the files to 'data' path, run :

  python prepare_data.py

4. Train

  • Train for pretrained model
  python train_pre.py
  • Train with Feature Transfer Learning
  python train_ftl.py

5. References

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