activity
20152022
most citedBenchmarking Classic and Learned Navigation in Complex 3D Environments

41 citations · 57 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV20228 cited

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…

cs.CV2020

Efficient Initial Pose-graph Generation for Global SfM

Daniel Barath, Dmytro Mishkin, Ivan Eichhardt +2

We propose ways to speed up the initial pose-graph generation for global Structure-from-Motion algorithms. To avoid forming tentative point correspondences by FLANN and geometric v…

cs.CV20208 cited

Differentiable Data Augmentation with Kornia

Jian Shi, Edgar Riba, Dmytro Mishkin +2

In this paper we present a review of the Kornia differentiable data augmentation (DDA) module for both for spatial (2D) and volumetric (3D) tensors. This module leverages different…

cs.DL2020

ArXiving Before Submission Helps Everyone

Dmytro Mishkin, Amy Tabb, Jiri Matas

We claim, and present evidence, that allowing arXiv publication before a conference or journal submission benefits researchers, especially early career, as well as the whole scient…

cs.CV2020

Image Matching across Wide Baselines: From Paper to Practice

Yuhe Jin, Dmytro Mishkin, Anastasiia Mishchuk +4

We introduce a comprehensive benchmark for local features and robust estimation algorithms, focusing on the downstream task -- the accuracy of the reconstructed camera pose -- as o…

cs.CV2019

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

Edgar Riba, Dmytro Mishkin, Daniel Ponsa +2

This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems. The pa…