Jason37437/Doc-Protocol-Data

Doc Protocol Data

The 4 cross-domain test sets (T-SROIE, OSTF, TPIC-13, RTM). All samples in the cross-domain test sets are cropped to 512 × 512 patches without additional compression. The cross-domain test sets have more diverse forgery sources, including AIGC-based text editing models and manual manipulation.

This dataset is used in the paper RiSE: Residual Subspace Expert for Generalizable Text-Centric Image Forgery Localization. Code is available at https://github.com/KahimWong/RiSE.

Cross-domain test sets

Dataset	Split	Domain	#Samples	Description
T-SROIE [Wang et al., 2022b]	Test	Cross-domain	1,579	Scanned receipts tampered using the AIGC text editing model SR-Net.
OSTF [Qu et al., 2025]	Test	Cross-domain	3,046	Natural scene text images tampered using eight different AIGC-based text editing models.
TPIC-13 [Wang et al., 2022a]	Test	Cross-domain	589	Naturally captured scene-text images tampered using the AIGC text editing model SR-Net.
RTM [Luo et al., 2025]	Test	Cross-domain	3,444	Document images with both synthetic and manual manipulations, covering copy-move, splicing, print, and erasure edits across diverse document types such as scanned forms.

Citation

If you use this dataset, please cite:

@article{du2025forensichub,
  title={ForensicHub: A unified benchmark \& codebase for all-domain fake image detection and localization},
  author={Bo Du and Xuekang Zhu and Xiaochen Ma and Chenfan Qu and Kaiwen Feng and Zhe Yang and Chi-Man Pun and Jian Liu and Ji-Zhe Zhou},
  journal={Advances in Neural Information Processing Systems},
  year={2025}
}