Midv806 2021 Best -

The search for a single paper titled "MIDV806 2021" identifies a significant family of research papers released in involving the (Mobile Identity Document Video) datasets, most notably

. While "MIDV-806" exists as a benchmark dataset, the foundational paper released in 2021 that describes this comprehensive framework is

"MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysis." Primary Research Paper (2021)

MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysis

K.B. Bulatov, E.V. Emelianova, D.V. Tropin, N.S. Skoryukina, Y.S. Chernyshova, A.V. Sheshkus, S.A. Usilin, et al. Publication Date: July 1, 2021 (ArXiv) Paper Overview & Dataset Scope MIDV-2020 paper

addresses the scarcity of public data for identity document recognition caused by security and privacy restrictions. It introduces a massive, richly annotated dataset of mock identity documents with unique, artificially generated text fields and faces. Total Images: 72,409 annotated images. Composition: 1,000 video clips captured via smartphones. 2,000 scanned images 1,000 photos of 1,000 unique physical documents. Document Types: midv806 2021

Includes 10 types of documents, such as identity cards and passports from various countries. Key Research Objectives & Benchmarks

The 2021 paper establishes baseline results for several critical document analysis tasks: Document Detection & Identification:

Locating the quadrangle boundaries of a document in unconstrained environments. Text Field Recognition:

Using systems like Tesseract to evaluate accuracy at both character and field levels. Face Detection:

Evaluating Multi-Task Cascaded Convolutional Neural Networks (MTCNN) on document photos. Semantic Segmentation: Separating the document body from complex backgrounds. Related 2021 Dataset Extensions The search for a single paper titled "MIDV806

In addition to the main MIDV-2020 paper, the team released specialized subsets and challenges in 2021: MIDV-LAIT (2021):

A dataset specifically for documents featuring Perso-Arabic, Thai, and Indian scripts, presented at ICDAR 2021. DLC-2021 (Document Liveness Challenge):

Focused on liveness detection and forensic analysis to prevent "rebroadcast" attacks (capturing a screen or printed copy). technical summary of the baseline results or information on how to download the dataset

It looks like you’re referencing a solid feature with the identifier midv806 2021.

Based on context, this is likely related to MIDV (Mobile Identity Document Video) datasets — specifically the MIDV-806 dataset from 2021. A robust feature extraction method used for document

The “solid feature” could refer to:

  1. A robust feature extraction method used for document analysis on the MIDV-806 dataset (e.g., keypoint detection, textural features, or deep features that are stable under video conditions).
  2. A published paper or technical report from 2021 that presents a “solid” (i.e., reliable or state-of-the-art) feature for mobile document recognition, tested on MIDV-806.

If you need a precise answer, could you clarify:

Let me know, and I’ll give you the exact technical breakdown.

5. Impact Assessment

3.1. Data Source

The MIDV-806 dataset consists of 806 high-resolution images. The documents included in the dataset simulate real-world identity cards, driver's licenses, and financial documents (such as checks or invoices). While some images may be derived from video frames of previous MIDV datasets, the 2021 release focuses on curated, static images optimized for training deep learning models.

The Future: Beyond 2021

As of late 2024, the research community is already discussing the next iteration (potentially MIDV2000 or MIDV-Synth). However, MIDV806 2021 remains the most widely cited benchmark. As synthetic data generation improves, we will likely see hybrid datasets built on the structure of MIDV806 but with infinite variations of documents generated by GANs (Generative Adversarial Networks).

Performance and driving dynamics

Tuned for urban agility rather than outright sportiness:

Interior and comfort

The cabin prioritizes practicality and user-friendly tech: