activity
20162019
most citedCompression Artifacts Removal Using Convolutional Neural Networks

123 citations · 328 across the 9 of their papers we have counts for

collaborators

11 papers

eess.IV2019

Evaluation of 4D Light Field Compression Methods

David Barina, Tomas Chlubna, Marek Solony +2

Light field data records the amount of light at multiple points in space, captured e.g. by an array of cameras or by a light-field camera that uses microlenses. Since the storage a…

cs.CV2017

The Parallel Algorithm for the 2-D Discrete Wavelet Transform

David Barina, Pavel Najman, Petr Kleparnik +2

The discrete wavelet transform can be found at the heart of many image-processing algorithms. Until now, the transform on general-purpose processors (CPUs) was mostly computed usin…

eess.SP2017★ 2 cited

Simple Signal Extension Method for Discrete Wavelet Transform

David Barina, Pavel Zemcik, Michal Kula

Discrete wavelet transform of finite-length signals must necessarily handle the signal boundaries. The state-of-the-art approaches treat such boundaries in a complicated and inflex…

cs.PF2017★ 1 cited

Accelerating Discrete Wavelet Transforms on Parallel Architectures

David Barina, Michal Kula, Michal Matysek +1

The 2-D discrete wavelet transform (DWT) can be found in the heart of many image-processing algorithms. Until recently, several studies have compared the performance of such transf…

cs.CV2017

Accelerating Discrete Wavelet Transforms on GPUs

David Barina, Michal Kula, Michal Matysek +1

The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques. Until now, several papers compared the performance of such transfor…

cs.CV2017★ 88 cited

Comprehensive Data Set for Automatic Single Camera Visual Speed Measurement

Jakub Sochor, Roman Juránek, Jakub Špaňhel +4

In this paper, we focus on traffic camera calibration and a visual speed measurement from a single monocular camera, which is an important task of visual traffic surveillance. Exis…

cs.CV2016★ 27 cited

Camera Pose Estimation from Lines using Plücker Coordinates

Bronislav Přibyl, Pavel Zemčík, Martin Čadík

Correspondences between 3D lines and their 2D images captured by a camera are often used to determine position and orientation of the camera in space. In this work, we propose a no…

cs.CV2016★ 80 cited

Absolute Pose Estimation from Line Correspondences using Direct Linear Transformation

Bronislav Přibyl, Pavel Zemčík, Martin Čadík

This work is concerned with camera pose estimation from correspondences of 3D/2D lines, i. e. with the Perspective-n-Line (PnL) problem. We focus on large line sets, which can be e…

cs.CV2016★ 123 cited

Compression Artifacts Removal Using Convolutional Neural Networks

Pavel Svoboda, Michal Hradis, David Barina +1

This paper shows that it is possible to train large and deep convolutional neural networks (CNN) for JPEG compression artifacts reduction, and that such networks can provide signif…

cs.CV2016★ 6 cited

Parallel Wavelet Schemes for Images

David Barina, Michal Kula, Pavel Zemcik

In this paper, we introduce several new schemes for calculation of discrete wavelet transforms of images. These schemes reduce the number of steps and, as a consequence, allow to r…

cs.CV2016★ 1 cited

CNN for License Plate Motion Deblurring

Pavel Svoboda, Michal Hradis, Lukas Marsik +1

In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks in a situation where the blur kernels are pa…