Visual perception of ships has been attracting increasing attention in the fields of computer vision and ocean engineering. Despite the extensive work related to landmark detection of common objects, the role of landmarks in ship perception has been overlooked. In this paper, we aim to fill this gap by focusing on ship landmarks. Specifically, we give a comprehensive analysis of both the physical structure and deep features of ships, which finds that highlighted areas in feature maps correspond with structurally significant parts of ships. By summarizing the locations of such areas in ships, we define 20 ship landmarks and build the Ship Landmark Dataset (SLAD), the first ship dataset with landmark annotations. We also provide a benchmark for ship landmark detection by evaluating state-of-the-art landmark detection methods on the newly built SLAD. Moreover, we showcased several applications of ship landmarks, including ship recognition, ship image generation, key area detection for ships, and ship detection. Project web page: https://vsislab.github.io/Ships_VSIS/.


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    Titel :

    Ship Landmark: An Informative Ship Image Annotation and Its Applications


    Beteiligte:
    Zhang, Mingxin (Autor:in) / Zhang, Qian (Autor:in) / Song, Ran (Autor:in) / Rosin, Paul L. (Autor:in) / Zhang, Wei (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.11.2024


    Format / Umfang :

    9360165 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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