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https://github.com/bradyfu/dvg
[NeurIPS 2019] Dual Variational Generation for Low Shot Heterogeneous Face Recognition
https://github.com/bradyfu/dvg
face-recognition heterogeneous-face-recognition pytorch
Last synced: 3 months ago
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[NeurIPS 2019] Dual Variational Generation for Low Shot Heterogeneous Face Recognition
- Host: GitHub
- URL: https://github.com/bradyfu/dvg
- Owner: BradyFU
- License: mit
- Created: 2019-08-19T02:02:30.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-11-13T03:12:40.000Z (over 1 year ago)
- Last Synced: 2023-11-14T03:36:40.055Z (over 1 year ago)
- Topics: face-recognition, heterogeneous-face-recognition, pytorch
- Language: Python
- Homepage:
- Size: 66.4 KB
- Stars: 116
- Watchers: 7
- Forks: 23
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Dual Variational Generation for Low Shot HFR
A PyTorch code of paper [Dual Variational Generation for Low Shot Heterogeneous Face Recognition](https://proceedings.neurips.cc/paper/2019/file/b5a1fc2085986034e448d2ccc5bb9703-Paper.pdf).
## Our Heterogeneous Face Recognition Works
✨ [**DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition**](https://arxiv.org/pdf/2009.09399.pdf)
- Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, and Ran He. **IEEE TPAMI 2021**
✨ [**Dual Variational Generation for Low Shot Heterogeneous Face Recognition**](https://proceedings.neurips.cc/paper/2019/file/b5a1fc2085986034e448d2ccc5bb9703-Paper.pdf)
- Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, and Ran He. **NeurIPS 2019**
✨ [**Towards Lightweight Pixel-Wise Hallucination for Heterogeneous Face Recognition**](https://ieeexplore.ieee.org/abstract/document/9971748)
- Chaoyou Fu, Xiaoqiang Zhou, Weizan He, and Ran He. **IEEE TPAMI 2022**
✨ [**Cross-Spectral Face Hallucination via Disentangling Independent Factors**](https://openaccess.thecvf.com/content_CVPR_2020/papers/Duan_Cross-Spectral_Face_Hallucination_via_Disentangling_Independent_Factors_CVPR_2020_paper.pdf)
- Boyan Duan, Chaoyou Fu, Yi Li, Xingguang Song, and Ran He. **CVPR 2020**
## News
The extension version of DVG is published in IEEE TPAMI 2021 ([DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition](https://arxiv.org/pdf/2009.09399.pdf)), and its code is released in https://github.com/BradyFU/DVG-Face.
The newly released extension version has more powerful performances than this version.
## Prerequisites
- Python 2.7
- Pytorch 0.4.1 & torchvision 0.2.1
## Train the generator
- Download LightCNN-29 model ([Google Drive](https://drive.google.com/file/d/1Jn6aXtQ84WY-7J3Tpr2_j6sX0ch9yucS/view)) pretrained on the MS-Celeb-1M dataset.
- Train the generator:
```
sh run_train_generator.sh
```
- Note that this is a simplified version of our original code:
1. The diversity loss and the adversarial loss in the paper are removed.
2. The distribution alignment loss is replaced by a Maximum Mean Discrepancy (MMD) loss.
- The generated results during training will be saved in `./results`.
## Generate images from noise
- Use the trained generator to sample 100,000 paired heterogeneous data:
```
Python val.py --pre_model './model/netG_model_epoch_50_iter_0.pth'
```
- The generated fake NIR and VIS images will be saved in `./fake_images/nir_noise` and `./fake_images/vis_noise`, respectively.
## Train the recognition model LightCNN-29
- Use the real data and the generated fake data to train lightcnn:
```
sh run_train_lightcnn.sh
```
## Performance
The performance on the 1-fold of CASIA NIR-VIS 2.0 dataset after running the above code:
Rank-1 | VR@FAR=0.1% | VR@FAR=0.01%
:---: | :---: | :---:
99.9% | 99.8% | 98.9%
## Citation
If you use our code for your research, please cite the following paper:
```
@article{fu2021dvg,
title={DVG-face: Dual variational generation for heterogeneous face recognition},
author={Fu, Chaoyou and Wu, Xiang and Hu, Yibo and Huang, Huaibo and He, Ran},
journal={IEEE TPAMI},
year={2021}
}
@inproceedings{fu2019dual,
title={Dual Variational Generation for Low-Shot Heterogeneous Face Recognition},
author={Fu, Chaoyou and Wu, Xiang and Hu, Yibo and Huang, Huaibo and He, Ran},
booktitle={NeurIPS},
year={2019}
}
@article{fu2022towards,
title={Towards Lightweight Pixel-Wise Hallucination for Heterogeneous Face Recognition},
author={Fu, Chaoyou and Zhou, Xiaoqiang and He, Weizan and He, Ran},
journal={IEEE TPAMI},
year={2022}
}
@inproceedings{duan2020cross,
title={Cross-spectral face hallucination via disentangling independent factors},
author={Duan, Boyan and Fu, Chaoyou and Li, Yi and Song, Xingguang and He, Ran},
booktitle={CVPR},
year={2020}
}
```