arXiv:2503.22417
DF2023: The Digital Forensics 2023 Dataset for Image Forgery Detection
원문 초록
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.
함께 살펴볼 논문
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SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
Learning Universal Features for Generalizable Image Forgery Localization
FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models
Deep Image Restoration For Image Anti-Forensics
Deep Image Composition Meets Image Forgery
Fusion Transformer with Object Mask Guidance for Image Forgery Analysis
토론
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