| | --- |
| | task_categories: |
| | - feature-extraction |
| | - image-classification |
| | - zero-shot-image-classification |
| | pretty_name: Perturbed Faces |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # Perturbed Faces |
| |
|
| | This dataset contains 1000 images from [CelebA dataset](!https://www.kaggle.com/datasets/jessicali9530/celeba-dataset). For each of the thousand images dataset also has [LowKey](https://openreview.net/forum?id=hJmtwocEqzc) perturbed version and [Fawkes](https://sandlab.cs.uchicago.edu/fawkes/) perturbed version. |
| | LowKey and Fawkes perturbed images have _attacked & _cloaked at the end of the filename respectively. |
| |
|
| |
|
| | | File Name | Version | |
| | |---------------------|--------------------------| |
| | | 000001.jpg | Original | |
| | | 000001_cloaked.png | Fawkes perturbed version | |
| | | 000001_attacked.png | LowKey perturbed version | |
| |
|
| |
|
| | The Fawkes perturbed images are created using CLI provided in the [github repository](https://github.com/Shawn-Shan/fawkes) with protection mode set to mid. The LowKey version of |
| | images are created using Python code provided with the paper. |
| |
|
| |
|
| | ## Citation |
| | If you found this work helpful for your research, please cite it as following: |
| | ``` |
| | @misc{2301.07315, |
| | Author = {Aaditya Bhat and Shrey Jain}, |
| | Title = {Face Recognition in the age of CLIP & Billion image datasets}, |
| | Year = {2023}, |
| | Eprint = {arXiv:2301.07315}, |
| | } |
| | ``` |
