Description

Sewer-ML is a sewer defect dataset. It contains 1.3 million images, from 75,618 videos collected from three Danish water utility companies over nine years. All videos have been annotated by licensed sewer inspectors following the Danish sewer inspection standard, Fotomanualen. This leads to consistent and reliable annotations, and a total of 17 annotated defect classes.
Date made available18 Jun 2021
Publishersciencedata.dk
Geographical coverageDenmark

Emneord

  • Sewer Defects
  • Sewer
  • Sewer Inspection
  • Multi-Label Image Classification
  • Defect Classification
  • Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and Benchmark

    Haurum, J. B. & Moeslund, T. B., 2021, (Accepted/In press) 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): IEEE, 12 p. (I E E E Conference on Computer Vision and Pattern Recognition. Proceedings).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    Open Access

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