vankey/RealText-V2

---
license: cc-by-nc-4.0
task_categories:
- image-segmentation
- text-classification
- visual-question-answering
language:
- en
- zh
- ar
- th
- ms
- id
tags:
- document-forgery-analysis
- forgery-detection
- multilingual
- document-analysis
- tampering-detection
size_categories:
- 10K<n<100K
---

# RealText-V2: A Large-Scale Multilingual Document Forgery Analysis Benchmark


## 💾 Dataset Description

**RealText-V2** is a large-scale multilingual document benchmark dataset purpose-built for multilingual text image forgery analysis, pioneering in both scale and annotation depth.

### Key Features

- **20K+ images**: A large-scale benchmark, surpassing existing document forgery analysis datasets by orders of magnitude
- **6 languages**: English, Chinese, Arabic, Thai, Malay, and Indonesian — spanning Latin, logographic, Arabic, and Thai script systems, each presenting unique forgery analysis challenges
- **6 domains**: Finance, education, healthcare, live streaming, e-commerce, and natural scenes
- **Multi-granularity forgery**: Character-level, word-level, and semantic-level tampering
- **Multi-source samples**: Real-world and AIGC-synthesized forgery samples covering diverse generation pipelines
- **Rich multi-task annotations**: Pixel-level localization masks, tampering type labels, and expert-level natural language explanations

### Competition Timeline
**ACM MM 2026 MGC: GenText-Forensics: Challenge on Explainable Forensics and Adversarial Generation for Text-Centric Images**

https://www.codabench.org/competitions/15805/

| Phase | Date |
| --- | --- |
| Competition Launch | April 17, 2026 |
| Training Data Release | April 20, 2026 |
| Evaluation Submission Opens | May 22, 2026 |
| Leaderboard Freeze | May 31, 2026 |
| Paper Submission Deadline | June 20, 2026 |
| ACM MM 2026, Rio de Janeiro | November 10–14, 2026 |

## 📊 Dataset Structure

```
RealText-V2/
├── train/
│ ├── image/ # Document images (.jpg for forged, .png for pristine)
│ │ ├── part000/ # Sharded at 1000 files per subdirectory
│ │ ├── part001/
│ │ └── ...
│ ├── mask/ # Binary tampering masks (forged only)
│ │ ├── part000/
│ │ └── ...
│ └── report/ # Structured forgery analysis reports (.md)
│ ├── part000/
│ ├── part001/
│ └── ...
├── doc_sample.png
└── metadata.parquet # Index file with sample metadata
```

> **Note:** The test split is withheld for the ongoing ACM MM 2026 competition and will be released after the competition concludes.

### Splits

| Split | Total | Black (Forged) | White (Pristine) |
|-------|-------|----------------|-------------------|
| train | 13,500 | 7,500 | 6,000 |

### Language Distribution (Train)

| Language | Code | Black (Forged) | White (Pristine) |
|----------|------|----------------|-------------------|
| English | en | 2,000 | 1,000 |
| Chinese | zh | 2,000 | 1,000 |
| Thai | th | 1,000 | 1,000 |
| Malay | ms | 1,000 | 1,000 |
| Indonesian | id | 1,000 | 1,000 |
| Arabic | ar | 500 | 1,000 |

## 📋 Data Fields

| Field | Description |
|-------|-------------|
| `sample_id` | Unique identifier (e.g., `GenText_Forensic_00000000`) |
| `language` | Full language name |
| `language_code` | ISO 639-1 code |
| `type` | `black` (forged) or `white` (pristine) |
| `image_file` | Image filename |
| `mask_file` | Mask filename (empty for white samples) |
| `has_mask` | Whether tampering mask exists |
| `report_file` | Report filename |
| `report_text` | Full report content |

## 📝 Report Format

Each report is a structured markdown document:

```markdown
# FORGERY ANALYSIS REPORT

**[Conclusion]:** FORGED / PRISTINE
**[RISK_SCORE]:** 0-100

### ANOMALY_001: [type] ([location])
[GROUNDING]: [x1, y1, x2, y2]
[REASON]: [explanation text]

## SUMMARY
[summary text]
```

## ⚖️ License

This dataset is released under CC-BY-NC-4.0 for research purposes only.

## 🙏 Acknowledgments

RealText-V2 is created for the ACM MM 2026 competition on document forgery analysis.