Journal of Infrared and Millimeter Waves, Volume. 43, Issue 6, 859(2024)
Progressive spatio-temporal feature fusion network for infrared small-dim target detection
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
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)