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    REVIEW

    Confusing Object Detection: A Survey

    Kunkun Tong1,#, Guchu Zou2,#, Xin Tan1,*, Jingyu Gong1, Zhenyi Qi2, Zhizhong Zhang1, Yuan Xie1, Lizhuang Ma1

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3421-3461, 2024, DOI:10.32604/cmc.2024.055327

    Abstract Confusing object detection (COD), such as glass, mirrors, and camouflaged objects, represents a burgeoning visual detection task centered on pinpointing and distinguishing concealed targets within intricate backgrounds, leveraging deep learning methodologies. Despite garnering increasing attention in computer vision, the focus of most existing works leans toward formulating task-specific solutions rather than delving into in-depth analyses of methodological structures. As of now, there is a notable absence of a comprehensive systematic review that focuses on recently proposed deep learning-based models for these specific tasks. To fill this gap, our study presents a pioneering review that covers… More >

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