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Detecting Image Attribution for Text-to-Image Diffusion Models in RGB and Beyond

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Detecting Image Attribution for Text-to-Image Diffusion Models in RGB and Beyond

Open in Colab

Katherine Xu$^{1}$, Lingzhi Zhang$^{2}$, Jianbo Shi$^1$
$^1$ University of Pennsylvania, $^2$ Adobe Inc.

🚀 Updates

  • 4/23/2024: Released a demo using EfficientFormer

Setup

  • Clone this repo
git clone https://github.com/k8xu/ImageAttribution.git
  • Install dependencies
conda create --name attribution python=3.10 -y
conda activate attribution
pip install opencv-python torch pillow

Demo

Download a torchscript checkpoint and place it under the specified folder.

Model Name Torchscript Folder Test Accuracy
efficientformer efficientformer_torchscript (118M) ./deployment/efficientformer 90.03%

We randomly sampled 10 test images per class, so you can quickly try our image attributor. Please check out ./images.

python demo.py --img {IMAGE PATH}

Citation

If you find our work useful, please cite our paper:

@article{xu2024detecting,
    title={Detecting Image Attribution for Text-to-Image Diffusion Models in RGB and Beyond},
    author={Xu, Katherine and Zhang, Lingzhi and Shi, Jianbo},
    journal={arXiv preprint arXiv:2403.19653},
    year={2024}
}

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Detecting Image Attribution for Text-to-Image Diffusion Models in RGB and Beyond

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