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20182023
most citedMIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream

105 citations · 262 across the 14 of their papers we have counts for

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12 papers · 1 filter

cs.CV2023★ 2 cited

Unfolder: Fast localization and image rectification of a document with a crease from folding in half

A. M. Ershov, D. V. Tropin, E. E. Limonova +2

Presentation of folded documents is not an uncommon case in modern society. Digitizing such documents by capturing them with a smartphone camera can be tricky since a crease can di…

cs.CV2021★ 57 cited

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

Konstantin Bulatov, Ekaterina Emelianova, Daniil Tropin +8

Identity documents recognition is an important sub-field of document analysis, which deals with tasks of robust document detection, type identification, text fields recognition, as…

cs.CV2021★ 15 cited

Advanced Hough-based method for on-device document localization

D. V. Tropin, A. M. Ershov, D. P. Nikolaev +1

The demand for on-device document recognition systems increases in conjunction with the emergence of more strict privacy and security requirements. In such systems, there is no dat…

cs.CV2020

ResNet-like Architecture with Low Hardware Requirements

Elena Limonova, Daniil Alfonso, Dmitry Nikolaev +1

One of the most computationally intensive parts in modern recognition systems is an inference of deep neural networks that are used for image classification, segmentation, enhancem…

cs.CV2020

Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices

Anton Trusov, Elena Limonova, Dmitry Slugin +2

Quantized low-precision neural networks are very popular because they require less computational resources for inference and can provide high performance, which is vital for real-t…

cs.CV2020

Fast Approximate Modelling of the Next Combination Result for Stopping the Text Recognition in a Video

Konstantin Bulatov, Nadezhda Fedotova, Vladimir V. Arlazarov

In this paper, we consider a task of stopping the video stream recognition process of a text field, in which each frame is recognized independently and the individual results are c…

cs.CV2020★ 22 cited

Approach for Document Detection by Contours and Contrasts

Daniil V. Tropin, Sergey A. Ilyuhin, Dmitry P. Nikolaev +1

This paper considers arbitrary document detection performed on a mobile device. The classical contour-based approach often fails in cases featuring occlusion, complex background, o…

cs.CV2020

Comparison of scanned administrative document images

Elena Andreeva, Vladimir V. Arlazarov, Oleg Slavin +1

In this work the methods of comparison of digitized copies of administrative documents were considered. This problem arises, for example, when comparing two copies of documents sig…

cs.CV2019

Training the Convolutional Neural Network with Statistical Dependence of the Response on the Input Data Distortion

Igor Janiszewski, Dmitry Slugin, Vladimir V. Arlazarov

The paper proposes an approach to training a convolutional neural network using information on the level of distortion of input data. The learning process is modified with an addit…

cs.CV2019★ 2 cited

Next integrated result modelling for stopping the text field recognition process in a video using a result model with per-character alternatives

Konstantin Bulatov, Boris Savelyev, Vladimir V. Arlazarov

In the field of document analysis and recognition using mobile devices for capturing, and the field of object recognition in a video stream, an important problem is determining the…

cs.CV2019★ 50 cited

MIDV-2019: Challenges of the modern mobile-based document OCR

Konstantin Bulatov, Daniil Matalov, Vladimir V. Arlazarov

Recognition of identity documents using mobile devices has become a topic of a wide range of computer vision research. The portfolio of methods and algorithms for solving such task…

cs.CV2018★ 105 cited

MIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream

Vladimir V. Arlazarov, Konstantin Bulatov, Timofey Chernov +1

A lot of research has been devoted to identity documents analysis and recognition on mobile devices. However, no publicly available datasets designed for this particular problem cu…