|
|
--- |
|
|
license: apache-2.0 |
|
|
task_categories: |
|
|
- token-classification |
|
|
- text-classification |
|
|
- image-text-to-text |
|
|
- object-detection |
|
|
language: |
|
|
- en |
|
|
size_categories: |
|
|
- 100K<n<1M |
|
|
tags: |
|
|
- Multimodal |
|
|
- manipulation-detection |
|
|
- media-forensics |
|
|
- deepfake-detection |
|
|
--- |
|
|
|
|
|
# Resource 📖 |
|
|
|
|
|
<h4 align="center"> |
|
|
<a href="https://arxiv.org/abs/2509.12653">[ACM MM Paper]</a> | <a href="https://huggingface.co/datasets/SJJ0854/SAMM">[SAMM HF]</a> | <a href="https://huggingface.co/datasets/SJJ0854/CAP">[CAP HF]</a> | <a href=" https://github.com/shen8424/SAMM-RamDG-CAP">[Github Code]</a> |
|
|
</h4> |
|
|
|
|
|
|
|
|
# Notes ⚠️ |
|
|
|
|
|
- If you want to import the CAP data into your own dataset, please refer to [this](https://github.com/shen8424/CAP). |
|
|
- If you want to run RamDG on datasets other than SAMM and use CNCL to incorporate external knowledge, please ensure to configure ```idx_cap_texts``` and ```idx_cap_images``` in the dataset jsons. |
|
|
- We have upgraded the SAMM JSON files. The latest versions (SAMM with CAP or without CAP) are available on July 24, 2025. Please download the newest version. |
|
|
|
|
|
# Brief introduction |
|
|
|
|
|
<div align="center"> |
|
|
<img src='./figures/teaser.png' width='90%'> |
|
|
</div> |
|
|
|
|
|
We present <b>SAMM</b>, a large-scale dataset for Detecting and Grounding Semantic-Coordinated Multimodal Manipulation. The official code has been released at [this](https://github.com/shen8424/SAMM-RamDG-CAP). |
|
|
|
|
|
**Dataset Statistics:** |
|
|
|
|
|
<div align="center"> |
|
|
<img src='./figures/samm_statistics.png' width='90%'> |
|
|
</div> |
|
|
|
|
|
|
|
|
# Annotations |
|
|
``` |
|
|
{ |
|
|
"text": "Lachrymose Terri Butler, whose letter prompted Peter Dutton to cancel Troy Newman's visa, was clearly upset.", |
|
|
"fake_cls": "attribute_manipulation", |
|
|
"image": "emotion_jpg/65039.jpg", |
|
|
"id": 13, |
|
|
"fake_image_box": [ |
|
|
665, |
|
|
249, |
|
|
999, |
|
|
671 |
|
|
], |
|
|
"cap_texts": { |
|
|
"Terri Butler": "Terri Butler Gender: Female, Occupation: Politician, Birth year: 1977, Main achievement: Member of Australian Parliament.", |
|
|
"Peter Dutton": "Peter Dutton Gender: Male, Occupation: Politician, Birth year: 1970, Main achievement: Australian Minister for Defence." |
|
|
}, |
|
|
"cap_images": { |
|
|
"Terri Butler": "Terri Butler", |
|
|
"Peter Dutton": "Peter Dutton" |
|
|
}, |
|
|
"idx_cap_texts": [ |
|
|
1, |
|
|
0 |
|
|
], |
|
|
"idx_cap_images": [ |
|
|
1, |
|
|
0 |
|
|
], |
|
|
"fake_text_pos": [ |
|
|
0, |
|
|
11, |
|
|
13, |
|
|
14, |
|
|
15 |
|
|
] |
|
|
} |
|
|
``` |
|
|
|
|
|
- `image`: The relative path to the original or manipulated image. |
|
|
- `text`: The original or manipulated text caption. |
|
|
- `fake_cls`: Indicates the type of manipulation (e.g., forgery, editing). |
|
|
- `fake_image_box`: The bounding box coordinates of the manipulated region in the image. |
|
|
- `fake_text_pos`: A list of indices specifying the positions of manipulated tokens within the `text` string. |
|
|
- `cap_texts`: Textual information extracted from CAP (Contextual Auxiliary Prompt) annotations. |
|
|
- `cap_images`: Relative paths to visual information from CAP annotations. |
|
|
- `idx_cap_texts`: A binary array where the i-th element indicates whether the i-th celebrity in `cap_texts` is tampered (1 = tampered, 0 = not tampered). |
|
|
- `idx_cap_images`: A binary array where the i-th element indicates whether the i-th celebrity in `cap_images` is tampered (1 = tampered, 0 = not tampered). |
|
|
|
|
|
# 🤗🤗🤗 Citation |
|
|
``` |
|
|
@misc{shen2025artificialmisalignmentdetectinggrounding, |
|
|
title={Beyond Artificial Misalignment: Detecting and Grounding Semantic-Coordinated Multimodal Manipulations}, |
|
|
author={Jinjie Shen and Yaxiong Wang and Lechao Cheng and Nan Pu and Zhun Zhong}, |
|
|
year={2025}, |
|
|
eprint={2509.12653}, |
|
|
archivePrefix={arXiv}, |
|
|
primaryClass={cs.CV}, |
|
|
url={https://arxiv.org/abs/2509.12653}, |
|
|
} |
|
|
``` |