Datasets:

SJJ0854
/

SAMM

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 📖

[ACM MM Paper] | [SAMM HF] | [CAP HF] | [Github Code]

Notes ⚠️

If you want to import the CAP data into your own dataset, please refer to this.
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

We present SAMM, a large-scale dataset for Detecting and Grounding Semantic-Coordinated Multimodal Manipulation. The official code has been released at this.

Dataset Statistics:

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}, 
}