Long-term visual localization in dynamic benthic environments: the SEALOC dataset, footprint-based ground truth, and visual place recognition benchmark.

Larsen MK, Pizarro O.

Open source

DOI: 10.3389/frobt.2026.1821019
Published: 2026-06-08
Container: Front Robot AI
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frobt.2026.1821019,
  title = {Long-term visual localization in dynamic benthic environments: the SEALOC dataset, footprint-based ground truth, and visual place recognition benchmark.},
  author = {Larsen MK and  Pizarro O.},
  year = {2026},
  journal = {Front Robot AI},
  doi = {10.3389/frobt.2026.1821019},
  url = {https://doi.org/10.3389/frobt.2026.1821019}
}

RIS

TY  - JOUR
TI  - Long-term visual localization in dynamic benthic environments: the SEALOC dataset, footprint-based ground truth, and visual place recognition benchmark.
AU  - Larsen MK
AU  -  Pizarro O.
PY  - 2026
JO  - Front Robot AI
DO  - 10.3389/frobt.2026.1821019
UR  - https://doi.org/10.3389/frobt.2026.1821019
ER  -

APA

MK, L., & O., P. (2026). Long-term visual localization in dynamic benthic environments: the SEALOC dataset, footprint-based ground truth, and visual place recognition benchmark.. Front Robot AI. https://doi.org/10.3389/frobt.2026.1821019

Source records

europe-pmc · retrieved 2026-11-10T11:54:22.491Z
doaj · retrieved 2026-11-10T11:54:22.488Z