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arXiv · 2503.22417

DF2023: The Digital Forensics 2023 Dataset for Image Forgery Detection

David Fischinger·Martin Boyer
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Abstract

The deliberate manipulation of public opinion, especially through altered images, which are frequently disseminated through online social networks, poses a significant danger to society. To fight this issue on a technical level we support the research community by releasing the Digital Forensics 2023 (DF2023) training and validation dataset, comprising one million images from four major forgery categories: splicing, copy-move, enhancement and removal. This dataset enables an objective comparison of network architectures and can significantly reduce the time and effort of researchers preparing datasets.

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BibTeXRIS

David Fischinger, Martin Boyer. 2025-03-28. DF2023: The Digital Forensics 2023 Dataset for Image Forgery Detection. https://doi.org/10.5281/zenodo.8215043%2010.5281%2Fzenodo.7326540

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