MARVEL: A large-scale image dataset for maritime vessels

Erhan Gundogdu, Berkan Solmaz, Veysel Yücesoy, Aykut Koç

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations


Fine-grained visual categorization has recently received great attention as the volumes of the labelled datasets for classification of specific objects, such as cars, bird species, and aircrafts, have been increasing. The collection of large datasets has helped vision based classification approaches and led to significant improvements in performances of the state-of-the-art methods. Visual classification of maritime vessels is another important task assisting naval security and surveillance applications. In this work, we introduce a large-scale image dataset for maritime vessels, consisting of 2 million user uploaded images and their attributes including vessel identity, type, photograph category and year of built, collected from a community website. We categorize the images into 109 vessel type classes and construct 26 superclasses by combining heavily populated classes with a semi-automatic clustering scheme. For the analysis of our dataset, extensive experiments have been performed, involving four potentially useful applications; vessel classification, verification, retrieval, and recognition. We report encouraging results for each application. The introduced dataset is publicly available.

Original languageEnglish (US)
Title of host publicationComputer Vision - 13th Asian Conference on Computer Vision, ACCV 2016, Revised Selected Papers
EditorsKo Nishino, Shang-Hong Lai, Vincent Lepetit, Yoichi Sato
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319541921
StatePublished - 2017
Externally publishedYes
Event13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan, Province of China
Duration: Nov 20 2016Nov 24 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10115 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th Asian Conference on Computer Vision, ACCV 2016
Country/TerritoryTaiwan, Province of China
City Taipei

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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