Awesome
CelebA HQ Face Identity and Attributes Recognition using PyTorch
This repository provides a CelebA HQ face identity and attribute recognition model using PyTorch.
- This dataset has been first introduced in the official PyTorch implementations for <b>Latent-HSJA</b>.
- The work is presented at ECCV 2022 Workshop on Adversarial Robustness in the Real World.
Datasets
Facial Identity Recognition Dataset
- There are 307 identities.
- Each identity has more than 15 images.
- There are 4,263 train images.
- There are 1,215 test images.
Face Gender Recognition Dataset
- There are 30,000 gender images.
- There are 11,057 male images.
- There are 18,943 female images.
- There are 23,999 train images.
- There are 6,001 test images.
Model Training Examples
Facial Identity Recognition Model
- Training source code
- Testing source code
- Test accuracy: <b>86.0082%</b>
Face Gender Recognition Dataset
- Training source code
- Testing source code
- Test accuracy: <b>98.4003%</b>
Citation
If this work can be useful for your research, please cite our paper:
<pre> @inproceedings{na2022unrestricted, title={Unrestricted Black-Box Adversarial Attack Using GAN with Limited Queries}, author={Na, Dongbin and Ji, Sangwoo and Kim, Jong}, booktitle={European Conference on Computer Vision}, pages={467--482}, year={2022}, organization={Springer} } </pre>