|
--- |
|
language: |
|
- en |
|
license: mit |
|
size_categories: |
|
- 10K<n<100K |
|
task_categories: |
|
- text-to-image |
|
- image-feature-extraction |
|
tags: |
|
- diffusion models |
|
- image copy detection |
|
dataset_info: |
|
features: |
|
- name: Name |
|
dtype: string |
|
- name: Level |
|
dtype: int64 |
|
- name: generated_images |
|
dtype: image |
|
- name: real_images |
|
dtype: image |
|
splits: |
|
- name: Test |
|
num_bytes: 2538590040.0 |
|
num_examples: 4000 |
|
- name: Train |
|
num_bytes: 22265208436.0 |
|
num_examples: 36000 |
|
download_size: 24773596239 |
|
dataset_size: 24803798476.0 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: Test |
|
path: data/Test-* |
|
- split: Train |
|
path: data/Train-* |
|
--- |
|
|
|
<p align="center"> |
|
<img src="https://huggingface.co/datasets/WenhaoWang/D-Rep/resolve/main/D-Rep.png" width="800"> |
|
</p> |
|
|
|
# Summary |
|
This is the dataset proposed in our paper [**Image Copy Detection for Diffusion Models**](https://arxiv.org/abs/2410.xxxxx) (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](https://huggingface.co/docs/datasets/en/installation) library first, by: |
|
``` |
|
pip install datasets |
|
``` |
|
Then it can be downloaded automatically with |
|
```python |
|
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](https://wangwenhao0716.github.io/), Dr. [Yifan Sun](https://yifansun-reid.github.io/), [Zhentao Tan](https://scholar.google.com.hk/citations?user=jDsfBUwAAAAJ) and Professor [Yi Yang](https://scholar.google.com/citations?user=RMSuNFwAAAAJ). |
|
|
|
# License |
|
|
|
We release our D-Rep under the [MIT license](https://opensource.org/license/mit). |
|
|
|
|
|
# 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). |