Awesome
This is the offical repository of the paper:
Unsupervised Face Recognition using Unlabeled Synthetic Data
Paper accepted at Face and Gesture 2023
Pretrained Models
Model | Images | LFW | AgeDB-30 | CFP-FP | CA-LFW | CP-LFW | Pretrained Model |
---|---|---|---|---|---|---|---|
USynthFace | 100K | 92.12 | 71.08 | 78.19 | 76.15 | 71.95 | download |
USynthFace | 200K | 91.93 | 71.23 | 78.03 | 76.73 | 72.27 | download |
USynthFace | 400K | 92.23 | 71.62 | 78.56 | 77.05 | 72.03 | download |
Requirements
Requirements for DiscoFaceGAN Image Generation:
- Python 3.6
- Tensorflow 1.12 with GPU support
We recommend creating a virtual environment with requirementsTF.txt
.
Download pretrained DiscoFaceGAN, strickly follow DiscoFaceGAN license and save in DiscoFaceGAN/pretrained/
.
Requirements for USynthFace Training
- pytorch 1.11.0
- torchvision 0.12.0
We recomment creating a virtual environment with requirementsTorch.txt
Training Dataset Preparation
To generate images run in DiscoFaceGAN/
:
generate_imgs.sh --save_path "save/path/of/unaligned/images"
To align images run:
align_imgs.sh --in_folder "path/to/image/folder" --out_folder "save/path/of/aligned/images"
Set datapath="../.."
in config/config.py
to folder with aligned DiscoFaceGAN images.
Evaluation Dataset Preparation
Download evaluation datasets from insightface in strict compliance with the license distribution. Evaluation datasets are available e.g. in the training dataset package CASIA-Webface as bin files.
Set eval_datasets="../.."
in config/config.py
to your unzipped folder which includes the bin files.
Train USynthFace
Change config/config.py
and train.sh
to your preferences and execute:
train.sh
To reproduce the results of the pretrained models, change number_of_images=
and output_dir=
in config/config.py
.
Evaluate USynthFace
In evaluation/
run:
CUDA_VISIBLE_DEVICES=0 python eval.py --model_folder "path/to/model/folder/" --rec_path "path/to/folder/with/bin/files"
Test log is saved in model_folder.
References:
If you use any of the code provided in this repository, please cite the following paper:
Citation
@inproceedings{DBLP:conf/fgr/BoutrosKFKD23,
author = {Fadi Boutros and
Marcel Klemt and
Meiling Fang and
Arjan Kuijper and
Naser Damer},
title = {Unsupervised Face Recognition using Unlabeled Synthetic Data},
booktitle = {17th {IEEE} International Conference on Automatic Face and Gesture
Recognition, {FG} 2023, Waikoloa Beach, HI, USA, January 5-8, 2023},
pages = {1--8},
publisher = {{IEEE}},
year = {2023},
url = {https://doi.org/10.1109/FG57933.2023.10042627},
doi = {10.1109/FG57933.2023.10042627},
}
License
This project is licensed under the terms of the Attribution-NonCommercial-ShareAlike 4.0
International (CC BY-NC-SA 4.0) license.
Copyright (c) 2021 Fraunhofer Institute for Computer Graphics Research IGD Darmstadt