---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: mask
    dtype: image
  splits:
  - name: cross_test
    num_bytes: 268272318
    num_examples: 3621
  download_size: 268291289
  dataset_size: 268272318
configs:
- config_name: default
  data_files:
  - split: cross_test
    path: data/cross_test-*
---

# AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics

This repository provides the processed **AutoSplice** benchmark dataset for image forgery detection and manipulation localization, formatted consistently with other benchmarks such as [KhangTruong/CocoGlide](https://huggingface.co/datasets/KhangTruong/CocoGlide), [KhangTruong/OpenSDID](https://huggingface.co/datasets/KhangTruong/OpenSDID), [KhangTruong/Casia-v2.0](https://huggingface.co/datasets/KhangTruong/Casia-v2.0), and [KhangTruong/Diffseg30k](https://huggingface.co/datasets/KhangTruong/Diffseg30k).

## Dataset Overview

- **Dataset Name:** AutoSplice (Forged_JPEG100 canonical baseline)
- **Split:** `cross_test`
- **Total Samples:** 3621
- **Generator:** DALL-E 2 language-image model guided by contextual text prompts
- **Columns:**
  - `image` (`Image`): The tampered image (lossless JPEG quality 100).
  - `mask` (`Image`): Single-channel ground-truth binary mask (`0` = pristine / background, `255` = tampered / spliced region). Samples with only black masks (no tampered regions) have been removed.

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("KhangTruong/AutoSplice", split="cross_test")

sample = dataset[0]
image = sample["image"]
mask = sample["mask"]

print(image.size, mask.size)
```

## Citation

```bibtex
@inproceedings{jia2023autosplice,
  title={AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics},
  author={Jia, Shan and Huang, Mingzhen and Zhou, Zhou and Ju, Yan and Cai, Jialing and Lyu, Siwei},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  pages={893--903},
  year={2023}
}
```

## License & Usage Notes
Released for non-commercial research and educational purposes in accordance with the original AutoSplice dataset terms.