The MIDV series was created to address the scarcity of public data for ID analysis due to privacy laws (GDPR) and security concerns. Researchers from Smart Engines and other institutions developed these datasets using with synthetic data and AI-generated faces to ensure they are safe for public research use.
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(e.g., on a label, in a manual, or on a specific website) The MIDV series was created to address the
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typically refers to a subset or specific iteration within the Mobile Identity Document Video (MIDV) family of datasets, most notably the MIDV-500 . These datasets are crucial for training and benchmarking computer vision models designed to recognize identity documents (IDs) like passports and driver's licenses via mobile device video streams. Overview of the MIDV Dataset Series
downloading/formatting the dataset for a project? AI can make mistakes, so double-check responses Copy Creating a public link... You can now share this thread with others Good response Bad response 17 sites MIDV-500: a dataset for identity document analysis and ... A lot of research has been devoted to identity documents analysis and recognition on mobile devices. However, no publicly availabl... КиберЛенинка Датасеты документов MIDV, DLC - Smart Engines Скачать MIDV-LAIT. MIDV-LAIT: a challenging dataset for recognition of IDs with Perso-Arabic, Thai, and Indian scripts // ICDAR 20... Smart Engines MIDV-DM: A Document-Oriented Dataset for Image Manipulation ... Additionally, MIDV-DM contains document images reflecting interventions typical of images taken from the Internet: the presence of... Компьютерная оптика MIDV-500: a dataset for identity document analysis and ... In this paper we present a Mobile Identity Document Video dataset (MIDV-500) consisting of 500 video clips for 50 different identi... КиберЛенинка MIDV-2020: a comprehensive benchmark dataset for identity ... The first dataset of the MIDV family was MIDV-500 [8], which contained 500 video clips of 50 identity doc- uments, 10 clips per do... Компьютерная оптика MIDV-2019: Challenges of the modern mobile-based document OCR Oct 12, 2019 —