Midv250 -

The primary challenge in identity document research is the scarcity of public data due to . MIDV-250 addresses this by using mock identity documents created from public domain templates. These documents contain artificially generated personal data, including unique text fields and synthetic faces, ensuring that researchers can train and test models without violating data protection laws. Dataset Composition

: Complex backgrounds that challenge document localization algorithms. midv250

The MIDV-UP dataset is just the latest branch of a family tree designed to solve the "data scarcity" problem in ID analysis: Core Focus Key Feature Initial benchmark 500 clips of 50 document types. Scale and complexity 1,000 unique mock documents with generated data. Multilingual support Focused on Perso-Arabic, Thai, and Indian scripts. Forensic security Specifically designed to detect and validate holograms. Why This Matters for Your AI Models If you are building a document recognition pipeline, the Smart Engines Research Team The primary challenge in identity document research is

refers to a specific subset of the larger Mobile Identity Document Video (MIDV) Multilingual support Focused on Perso-Arabic