Journal of Infrared and Millimeter Waves, Volume. 43, Issue 6, 859(2024)

Progressive spatio-temporal feature fusion network for infrared small-dim target detection

Dan ZENG1, Jian-Ming WEI1, Jun-Jie ZHANG1, Liang CHANG2, and Wei HUANG1、*
Author Affiliations
  • 1School of Communication and Information Engineering,Shanghai University,Shanghai 200444,China
  • 2Innovation Academy for Microsatellites,Chinese Academy of Sciences,Shanghai 201203,China
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    To avoid the accumulation of estimation errors from explicitly aligning multi-frame features in current infrared small-dim target detection algorithms, and to alleviate the loss of target features due to network downsampling, a progressive spatio-temporal feature fusion network is proposed. The network utilizes a progressive temporal feature accumulation module to implicitly aggregate multi-frame information and utilizes a multi-scale spatial feature fusion module to enhance the interaction between shallow detail features and deep semantic features. Due to the scarcity of multi-frame infrared dim target datasets, a highly realistic semi-synthetic dataset is constructed. Compared to the mainstream algorithms, the proposed algorithm improves the probability of detection by 4.69% and 4.22% on the proposed dataset and the public dataset, respectively.

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    Dan ZENG, Jian-Ming WEI, Jun-Jie ZHANG, Liang CHANG, Wei HUANG. Progressive spatio-temporal feature fusion network for infrared small-dim target detection[J]. Journal of Infrared and Millimeter Waves, 2024, 43(6): 859

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    Paper Information

    Category: Interdisciplinary Research on Infrared Science

    Received: Mar. 24, 2024

    Accepted: --

    Published Online: Dec. 13, 2024

    The Author Email: HUANG Wei (lyxhw@shu.edu.cn)

    DOI:10.11972/j.issn.1001-9014.2024.06.017

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