Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Lukasz Dabala"'
Publikováno v:
ICPR
Environmental protection is one of the main challenges facing society nowadays. Even with constantly growing awareness, not all of the sorting can be done by people themselves - the differences between materials are not visible to the human eye. For
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dface00a3b39aba8e19a6af96e0e3191
https://doi.org/10.1109/icpr48806.2021.9412737
https://doi.org/10.1109/icpr48806.2021.9412737
Autor:
Jacek Komorowski, Grzegorz Kurzejamski, Konrad Czarnota, Simon Lynen, Tomasz Trzcinski, Lukasz Dabala
Publikováno v:
Advanced Concepts for Intelligent Vision Systems ISBN: 9783030406042
ACIVS
ACIVS
In this paper, we present a framework for computing dense keypoint correspondences between images under strong scene appearance changes. Traditional methods, based on nearest neighbour search in the feature descriptor space, perform poorly when envir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e463228e98b0fa3c13c56e8acc7238d8
https://doi.org/10.1007/978-3-030-40605-9_42
https://doi.org/10.1007/978-3-030-40605-9_42
Autor:
Lukasz Dabala, Konrad Czarnota, Jacek Komorowski, Simon Lynen, Grzegorz Kurzejamski, Tomasz Trzcinski
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110086
ECCV Workshops (1)
ECCV Workshops (1)
Numerous computer vision applications rely on local feature descriptors, such as SIFT, SURF or FREAK, for image matching. Although their local character makes image matching processes more robust to occlusions, it often leads to geometrically inconsi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d55485552b4e4d0dc9230933f1e816de
https://doi.org/10.1007/978-3-030-11009-3_24
https://doi.org/10.1007/978-3-030-11009-3_24
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110208
ECCV Workshops (5)
ECCV Workshops (5)
In the recent years, a number of novel, deep-learning based, interest point detectors, such as LIFT, DELF, Superpoint or LF-Net was proposed. However there’s a lack of a standard benchmark to evaluate suitability of these novel keypoint detectors f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c83977729317773f1e6e2feab4d8c65
https://doi.org/10.1007/978-3-030-11021-5_45
https://doi.org/10.1007/978-3-030-11021-5_45