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  Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths

Hornakova, A., Kaiser, T., Swoboda, P., Rolinek, M., Rosenhahn, B., & Henschel, R. (2022). Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV 2021) (pp. 6310-6320). Piscataway, NJ: IEEE. doi:10.1109/ICCV48922.2021.00627.

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Genre: Conference Paper

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Locator:
https://doi.org/10.1109/ICCV48922.2021.00627 (Publisher version)
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OA-Status:
Closed Access
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OA-Status:
Green

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 Creators:
Hornakova, Andrea 1, Author
Kaiser, Timo 1, Author
Swoboda, Paul 1, Author
Rolinek, Michal2, Author           
Rosenhahn, Bodo 1, Author
Henschel, Roberto 1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Max Planck Research Group Autonomous Learning, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_2575693              

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Free keywords: Forschungsgruppe Martius
 Abstract: -

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Language(s): eng - English
 Dates: 2022-02-282022
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/ICCV48922.2021.00627
arXiv: 2108.10606
BibTex Citekey: 2021_MOT_Rolinek
 Degree: -

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Title: IEEE/CVF International Conference on Computer Vision (ICCV 2021)
Place of Event: Online
Start-/End Date: 2021-10-11 - 2021-10-17

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Title: 2021 IEEE/CVF International Conference on Computer Vision (ICCV 2021)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 6310 - 6320 Identifier: DOI: 10.1109/ICCV48922.2021
ISBN: 978-1-6654-2812-5
ISBN: 978-1-6654-2813-2
ISSN: 2380-7504
ISSN: 1550-5499