Midv-112 __full__
The dataset contains 112 unique document types, which gives the collection its name. These include a wide array of international identity cards, passports, and driving licenses from various countries. For each document type, the dataset provides video clips and individual frames captured on different mobile devices. This variety ensures that the algorithms developed using MIDV-112 can handle different layout structures, fonts, and security features common in global identity documents.
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The primary objective of MIDV-112 is to address the challenges of mobile document recognition. Unlike static scans, images captured via smartphones often suffer from perspective distortion, glare, motion blur, and varying lighting. By providing a diverse set of document types captured in these "in-the-wild" scenarios, the dataset allows developers to train and test systems that are robust enough for commercial and governmental applications.
In terms of technical composition, the dataset is divided into training and testing sets to ensure unbiased evaluation. It includes images with different backgrounds—ranging from neutral office settings to cluttered domestic environments—to simulate the unpredictability of mobile capture. The inclusion of documents with complex security backgrounds and transparent elements further pushes the boundaries of current recognition technology. The dataset contains 112 unique document types, which
MIDV-112, featuring Yua Mikami, is a 2023 MOODYZ studio production representing a significant high-production idol-themed release towards the end of the actress's career. Released on May 2, 2023, the 120-minute film blends cinematic storytelling with the "S-Class" idol persona, falling within the "Miss Idol" series.
A key feature of MIDV-112 is its focus on ground truth data. Each image in the dataset is meticulously annotated with the coordinates of the document boundaries and the textual information contained within the fields. This level of detail is essential for supervised learning, where a model needs to know exactly what it is looking at to improve its accuracy. Researchers use this data to evaluate tasks such as document detection, field localization, and optical character recognition. This variety ensures that the algorithms developed using
The document MIDV-112, also known as the MIDV-2020 dataset, is a specialized collection of document images designed to advance the field of automatic identity document analysis. Created by researchers at the Smart Engines Service and the Russian Academy of Sciences, it serves as a critical benchmark for developing algorithms that can recognize and process identity documents in diverse, real-world conditions.
For the industry, MIDV-112 facilitates the creation of more reliable remote identity verification (eKYC) solutions. As more services—from banking to car sharing—move toward digital onboarding, the ability to accurately verify a user's ID via a smartphone becomes paramount. Tools trained on datasets like MIDV-112 help reduce friction for users while maintaining high security standards against fraud and document tampering.
