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: A subset dedicated entirely to Image Manipulation Detection, training AI to spot forged, spliced, or digitally altered text on ID documents. Core Machine Learning Use Cases
The MIDV (Mobile Identity Document Video) dataset family, including MIDV-500, MIDV-2019, and MIDV-2020, offers free access to video clips for document analysis and OCR research, available on platforms like arXiv and GitHub. The datasets provide extensive, annotated video clips focusing on ID cards and passports captured in varying conditions. Access the MIDV-500 dataset and conversion scripts on GitHub . As with any online search, concerns about safety
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Building an AI model capable of scanning a passport or driver's license using a smartphone camera requires thousands of sample images. However, because real identity documents contain highly sensitive personal data, developers cannot simply scrape them from the internet. To bypass this legal hurdle, researchers created the MIDV datasets using mock data and artificially generated faces. The framework has evolved across several major versions:
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