Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Bureš, Lukáš | |
| dc.contributor.author | Müller, Luděk | |
| dc.date.accessioned | 2022-03-28T10:00:28Z | - |
| dc.date.available | 2022-03-28T10:00:28Z | - |
| dc.date.issued | 2021 | |
| dc.identifier.citation | BUREŠ, L. MÜLLER, L. Semantic Segmentation in the Task of Long-Term Visual Localization. In 6th International Conference, ICR 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings. Cham: Springer, 2021. s. 27-39. ISBN: 978-3-030-87724-8 , ISSN: 0302-9743 | cs |
| dc.identifier.isbn | 978-3-030-87724-8 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | 2-s2.0-85116430820 | |
| dc.identifier.uri | http://hdl.handle.net/11025/47257 | |
| dc.format | 13 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Springer | en |
| dc.relation.ispartofseries | 6th International Conference, ICR 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings | en |
| dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
| dc.rights | © Springer | en |
| dc.title | Semantic Segmentation in the Task of Long-Term Visual Localization | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | ConferenceObject | en |
| dc.rights.access | restrictedAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | In this paper, it is discussed the problem of long-term visual localization with a using of the Aachen Day-Night dataset. Our experiments confirmed that carefully fine-tuning parameters of the Hierarchical Localization method can lead to enhance the visual localization accuracy. Next, our experiments show that it is possible to find an image’s area that does not add any valuable information in long-term visual localization and can be removed without losing the localization accuracy. The approach of using the method of semantic segmentation for preprocessing helped to achieve comparable state-of-the-art results in the Aachen Day-Night dataset. | en |
| dc.subject.translated | Long-term visual localization | en |
| dc.subject.translated | Semantic segmentation | en |
| dc.subject.translated | SuperPoint | en |
| dc.subject.translated | SuperGlue | en |
| dc.subject.translated | HRNet-OCR | en |
| dc.identifier.doi | 10.1007/978-3-030-87725-5_3 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.document-number | 711832900003 | |
| dc.identifier.obd | 43933460 | |
| dc.project.ID | LO1506/PUNTIS - Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost | cs |
| Vyskytuje se v kolekcích: | Konferenční příspěvky / Conference Papers (KKY) OBD | |
Soubory připojené k záznamu:
| Soubor | Velikost | Formát | |
|---|---|---|---|
| Bureš-Müller2021_Chapter_SemanticSegmentationInTheTaskO.pdf | 1,57 MB | Adobe PDF | Zobrazit/otevřít Vyžádat kopii |
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