Datasets:
Name
stringlengths 9
9
| Level
int64 0
5
| generated_images
imagewidth (px) 512
512
| real_images
imagewidth (px) 150
8.1k
|
---|---|---|---|
CAP000008 | 2 | ||
CAP000013 | 4 | ||
CAP000018 | 0 | ||
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CAP000949 | 4 |
Summary
This is the dataset proposed in our paper Image Copy Detection for Diffusion Models (NeurIPS 2024).
D-Rep consists of 40, 000 image-replica pairs, in which each replica is generated by a diffusion model. The 40, 000 image-replica pairs are manually labeled with 6 replication levels ranging from 0 (no replication) to 5 (total replication). We divide D-Rep into a training set with 90% (36, 000) pairs and a test set with the remaining 10% (4, 000) pairs.
Download
Automatical
Install the datasets library first, by:
pip install datasets
Then it can be downloaded automatically with
from datasets import load_dataset
dataset = load_dataset('WenhaoWang/D-Rep')
Manual
You can also download each file by wget
:
wget https://huggingface.co/datasets/WenhaoWang/D-Rep/resolve/main/training_pairs.tar
wget https://huggingface.co/datasets/WenhaoWang/D-Rep/resolve/main/test_pairs.tar
wget https://huggingface.co/datasets/WenhaoWang/D-Rep/resolve/main/labels.csv
Curators
D-Rep is created by Wenhao Wang, Dr. Yifan Sun, Zhentao Tan and Professor Yi Yang.
License
We release our D-Rep under the CC-BY-NC-4.0 license.
Helpful Links
The project homepage: https://icdiff.github.io/
The code of image copy detection for diffusion models: https://github.com/WangWenhao0716/PDF-Embedding
The official reviews of our paper: https://openreview.net/forum?id=gvlOQC6oP1
The Arxiv: https://arxiv.org/abs/2409.19952
Citation
@article{wang2024icdiff,
title={Image Copy Detection for Diffusion Models},
author={Wang, Wenhao and Sun, Yifan and Tan, Zhentao and Yang, Yi},
booktitle={Thirty-eighth Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=gvlOQC6oP1}
}
Contact
If you have any questions, feel free to contact Wenhao Wang (wangwenhao0716@gmail.com).
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