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The first visual object tracking segmentation VOTS2023 challenge results
University of Ljubljana, Slovenia.
Czech Technical University, Czech Republic.
Eth Zürich, Switzerland.
Linköping University, Sweden.
Show others and affiliations
2023 (English)In: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW), Institute of Electrical and Electronics Engineers Inc. , 2023, p. 1788-1810Conference paper, Published paper (Refereed)
Abstract [en]

The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2023. p. 1788-1810
Series
International Conference on Computer Vision Workshops (ICCV Workshops)
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:umu:diva-220443DOI: 10.1109/ICCVW60793.2023.00195Scopus ID: 2-s2.0-85175967599ISBN: 9798350307443 (electronic)OAI: oai:DiVA.org:umu-220443DiVA, id: diva2:1837264
Conference
International Conference on Computer Vision, Paris, France, October 2-6, 2023
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Available from: 2024-02-13 Created: 2024-02-13 Last updated: 2024-02-13Bibliographically approved

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Tran, Khanh-TungVu, Xuan-SonBjörklund, Johanna

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf