activity
20182023
most citedAdvanced Hough-based method for on-device document localization

15 citations · 40 across the 10 of their papers we have counts for

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Showing 2020 · cs.CVShow all

7 papers · 2 filters

cs.CV2020★ 1 cited

Illumination Estimation Challenge: experience of past two years

Egor Ershov, Alex Savchik, Ilya Semenkov +15

Illumination estimation is the essential step of computational color constancy, one of the core parts of various image processing pipelines of modern digital cameras. Having an acc…

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

Line detection via a lightweight CNN with a Hough Layer

Lev Teplyakov, Kirill Kaymakov, Evgeny Shvets +1

Line detection is an important computer vision task traditionally solved by Hough Transform. With the advance of deep learning, however, trainable approaches to line detection beca…

cs.CV2020

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★ 5 cited

Computational optimization of convolutional neural networks using separated filters architecture

Elena Limonova, Alexander Sheshkus, Dmitry Nikolaev

This paper considers a convolutional neural network transformation that reduces computation complexity and thus speedups neural network processing. Usage of convolutional neural ne…