datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Image_Forgery_Localization_DatasetsForgeryVCR
ForgeryVCR Data
This repository stores the preprocessed 832-size assets used by the public
ForgeryVCR training and evaluation workflow.
datasets/
├── train/
│ ├── sft/ # CASIA v2 archives for expert selection and Agent SFT
│ └── rl/ # IMD2020 and FantasticReality archives for GRPO
└── test/ # public evaluation benchmark archives
Tampered-set JSON files use paths relative to their own dataset directory, for
example ./forged/example.png and ./gt/example_gt.png.… See the full description on the dataset page: https://huggingface.co/datasets/ForgeryVCR-Team/ForgeryVCR.sifta-document-forgery-datasetrecod-forgeryForgeryGPT
Dataset Overview
This repository contains sample datasets used across different stages of our framework, including Mask-Text Alignment Pre-training, Task-Specific Instruction Tuning, and Explainability Analysis. Below is a structured description of the contents:
1. Mask-Text Alignment Pre-training: Sample Dataset
This section provides examples used for the Mask-Text Alignment Pre-training phase.
qa_pairs_pretrain_mask_sample.json: A JSON file containing… See the full description on the dataset page: https://huggingface.co/datasets/fanrui00/ForgeryGPT.Full-LibriSpeech-CopyMove-Forgery-Dataset
Full LibriSpeech Copy–Move Forgery Dataset
📘 Overview
The Full LibriSpeech Copy–Move Forgery Dataset is designed for advancing research in audio forgery detection and tampering localization. It focuses on the challenging task of copy–move forgeries, where segments from a single audio recording are duplicated and relocated within the same file.
The dataset provides speaker-disjoint splits, detailed temporal annotations, and multiple levels of forgery intensity to ensure… See the full description on the dataset page: https://huggingface.co/datasets/TheAnalyzer/Full-LibriSpeech-CopyMove-Forgery-Dataset.image-forgery-modelAI-Forgeryfrom huggingface_hub import HfApi
api = HfApi()
api.upload_large_folder(
repo_id="liyu0x/AI-Forgery",
repo_type="dataset",
folder_path="./AI-Forgery",
)
Forgery_detection