8 citations · 11 across the 10 of their papers we have counts for
13 papers
Ukrainian Visual Word Sense Disambiguation Benchmark
Yurii Laba, Yaryna Mohytych, Ivanna Rohulia +4
This study presents a benchmark for evaluating the Visual Word Sense Disambiguation (Visual-WSD) task in Ukrainian. The main goal of the Visual-WSD task is to identify, with minima…
DeVOS: Flow-Guided Deformable Transformer for Video Object Segmentation
Volodymyr Fedynyak, Yaroslav Romanus, Bohdan Hlovatskyi +4
The recent works on Video Object Segmentation achieved remarkable results by matching dense semantic and instance-level features between the current and previous frames for long-ti…
Global Motion Understanding in Large-Scale Video Object Segmentation
Volodymyr Fedynyak, Yaroslav Romanus, Oles Dobosevych +2
In this paper, we show that transferring knowledge from other domains of video understanding combined with large-scale learning can improve robustness of Video Object Segmentation…
Is Mapping Necessary for Realistic PointGoal Navigation?
Ruslan Partsey, Erik Wijmans, Naoki Yokoyama +3
Can an autonomous agent navigate in a new environment without building an explicit map? For the task of PointGoal navigation ('Go to , ') under idealized settings (no RGB-D…
OpenGlue: Open Source Graph Neural Net Based Pipeline for Image Matching
Ostap Viniavskyi, Mariia Dobko, Dmytro Mishkin +1
We present OpenGlue: a free open-source framework for image matching, that uses a Graph Neural Network-based matcher inspired by SuperGlue \cite{sarlin20superglue}. We show that in…
Towards realistic symmetry-based completion of previously unseen point clouds
Taras Rumezhak, Oles Dobosevych, Rostyslav Hryniv +3
3D scanning is a complex multistage process that generates a point cloud of an object typically containing damaged parts due to occlusions, reflections, shadows, scanner motion, sp…
Minimal Solvers for Single-View Lens-Distorted Camera Auto-Calibration
Yaroslava Lochman, Oles Dobosevych, Rostyslav Hryniv +1
This paper proposes minimal solvers that use combinations of imaged translational symmetries and parallel scene lines to jointly estimate lens undistortion with either affine recti…
LID 2020: The Learning from Imperfect Data Challenge Results
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…
Direct and inverse spectral problems for rank-one perturbations of self-adjoint operators
Oles Dobosevych, Rostyslav Hryniv
For a given self-adjoint operator with discrete spectrum, we completely characterize possible eigenvalues of its rank-one perturbations~ and discuss the inverse problem of r…
Weakly-Supervised Segmentation for Disease Localization in Chest X-Ray Images
Ostap Viniavskyi, Mariia Dobko, Oles Dobosevych
Deep Convolutional Neural Networks have proven effective in solving the task of semantic segmentation. However, their efficiency heavily relies on the pixel-level annotations that…
Spectra of rank-one perturbations of self-adjoint operators
Oles Dobosevych, Rostyslav Hryniv
We characterize possible spectra of rank-one perturbations B of a self-adjoint operator A with discrete spectrum and, in particular, prove that the spectrum of B may include any nu…
NoPeopleAllowed: The Three-Step Approach to Weakly Supervised Semantic Segmentation
Mariia Dobko, Ostap Viniavskyi, Oles Dobosevych
We propose a novel approach to weakly supervised semantic segmentation, which consists of three consecutive steps. The first two steps extract high-quality pseudo masks from image-…
CNN-CASS: CNN for Classification of Coronary Artery Stenosis Score in MPR Images
Mariia Dobko, Bohdan Petryshak, Oles Dobosevych
To decrease patient waiting time for diagnosis of the Coronary Artery Disease, automatic methods are applied to identify its severity using Coronary Computed Tomography Angiography…