http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/publicaciones/Publicacion/2023-2026

Literals

  • ou:urlScopus
  • ou:urlOrcid
  • bibo:page_range
    • 10-16
  • dcterms:creator
    • Saunders K.
  • dcterms:title
    • Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps
  • ou:eid
    • 2-s2.0-85162072792
  • ou:bibtex
    • @inproceedings{033c1bb6af4a42c2b1894b2a9d449fd2, title = 'Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps', abstract = 'Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture complexity. This paper shows that state-of-the-art performance can also be achieved by improving the learning process rather than increasing model complexity. More specifically, we propose (i) disregarding small potentially dynamic objects when training, and (ii) employing an appearance-based approach to separately estimate object pose for truly dynamic objects. We demonstrate that these simplifications reduce GPU memory usage by 29% and result in qualitatively and quantitatively improved depth maps.', keywords = 'Training, Computer vision, Image analysis, Estimation, Graphics processing units, Computer architecture, Complexity theory, Computer vision, Autonomous vehicles, 3D/stereo scene analysis, Vision and Scene Understanding', author = 'Kieran Saunders and George Vogiatzis and Manso, {Luis J.}', note = 'Funding Information: Most experiments were run on Aston EPS Machine Learning Server, funded by the EPSRC Core Equipment Fund, Grant EP/V036106/1. Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023 ; Conference date: 26-04-2023 Through 27-04-2023', year = '2023', month = may, day = '25', doi = '10.48550/arXiv.2206.03799', language = 'English', isbn = '979-8-3503-0122-9', series = 'Proceedings of IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)', publisher = 'IEEE', pages = '10--16', editor = 'Lopes, {Ana C.} and Gabriel Pires and Pinto, {Vitor H.} and Lima, {Jose L.} and Pedro Fonseca', booktitle = '2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)', address = 'United States', }
  • ou:tipoPublicacion
    • Conference Paper
  • dcterms:publisher
    • 2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023
  • bibo:doi
    • 10.1109/icarsc58346.2023.10129564
  • vcard:url
  • vivo:identifier
    • 2023-2026
  • bibo:isbn
    • 9798350301212
  • fabio:hasPublicationYear
    • 2023
  • dcterms:contributor
    • Saunders K., Vogiatzis G., Manso L.J.
  • ou:vecesCitado
    • 0

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