| # Fake Image Dataset | |
| Fake Image Dataset is now open-sourced at [huggingface (InfImagine Organization)](https://huggingface.co/datasets/InfImagine/FakeImageDataset/tree/main/ImageData/train). ↗ It consists of two folders, *ImageData* and *MetaData*. *ImageData* contains the compressed packages of the Fake Image Dataset, while *MetaData* contains the labeling information of the corresponding data indicating whether they are real or fake. | |
| Why we need Fake Image Dataset and Sentry-Image? | |
| * 🧐 Recent [study](https://arxiv.org/abs/2304.13023) have shown that humans struggle significantly to distinguish real photos from AI-generated ones, with a misclassification rate of **38.7%**. | |
| * 🤗 To help people confirm whether the images they see are real images or AI-generated images, we launched the Sentry-Image project. | |
| * 💻 Sentry-Image is an open source project which provides the SOTA fake image detection models in [Sentry-Image Leaderboard](http://sentry.infimagine.com/) to detect whether the image provided is an AI-generated or real image. | |
| Stay tuned for this project! Feel free to contact [contact@infimagine.com](contact@infimagine.com)! 😆 | |
| ## How to Download | |
| ```shell | |
| git lfs install | |
| git clone https://huggingface.co/datasets/InfImagine/FakeImageDataset | |
| ``` | |
| ## Sub Dataset | |
| ### Fake2M Dataset | |
| | Dataset | SD-V1.5Real-dpms-25 | IF-V1.0-dpms++-25 | StyleGAN3 | | |
| | ----------- | :-----------: | :-----------: | :-----------: | | |
| | Generator | Diffusion | Diffusion | GAN | | |
| | Numbers | 1M | 1M | 87K | | |
| | Resolution | 512 | 256 | (>=512) | | |
| | Caption | CC3M-Train | CC3M-Train | - | | |
| | ImageData Path | ImageData/train/SDv15R-CC1M | ImageData/train/IF-CC1M | ImageData/train/stylegan3-80K | | |
| | MetaData Path | MetaData/train/SDv15R-CC1M.csv | MetaData/train/IF-CC1M.csv | MetaData/train/stylegan3-80K.csv | | |
| ## License | |
| This project is open-sourced under the [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0). These weights and datasets are fully open for academic research and can be used for commercial purposes with official written permission. If you find our open-source models and datasets useful for your business, we welcome your donation to support the development of the next-generation Sentry-Image model. Please contact [contact@infimagine.com](contact@infimagine.com) for commercial licensing and donation inquiries. | |
| ## Citation | |
| The code and model in this repository is mostly developed for or derived from the paper below. Please cite it if you find the repository helpful. | |
| ``` | |
| @misc{sentry-image-leaderboard, | |
| title = {Sentry-Image Leaderboard}, | |
| author = {Zeyu Lu, Di Huang, Chunli Zhang, Chengyue Wu, Xihui Liu, Lei Bai, Wanli Ouyang}, | |
| year = {2023}, | |
| publisher = {InfImagine, Shanghai AI Laboratory}, | |
| howpublished = "\url{https://github.com/Inf-imagine/Sentry}" | |
| }, | |
| @misc{lu2023seeing, | |
| title = {Seeing is not always believing: Benchmarking Human and Model Perception of AI-Generated Images}, | |
| author = {Zeyu Lu, Di Huang, Lei Bai, Jingjing Qu, Chengyue Wu, Xihui Liu, Wanli Ouyang}, | |
| year = {2023}, | |
| eprint = {2304.13023}, | |
| archivePrefix = {arXiv}, | |
| primaryClass = {cs.AI} | |
| } | |
| ``` |