Asymmetric Contextual Modulation for Infrared Small Target Detection

Single-frame infrared small target detection remains a challenge not only due to the scarcity of intrinsic target characteristics but also because of lacking a public dataset. In this paper, we first contribute an open dataset with high-quality annotations to advance the research in this field. We a...

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Bibliographic Details
Published inProceedings / IEEE Workshop on Applications of Computer Vision pp. 949 - 958
Main Authors Dai, Yimian, Wu, Yiquan, Zhou, Fei, Barnard, Kobus
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2021
Subjects
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Computer vision
Conferences
Modulation
Object detection
Semantics
Technological innovation
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Summary:Single-frame infrared small target detection remains a challenge not only due to the scarcity of intrinsic target characteristics but also because of lacking a public dataset. In this paper, we first contribute an open dataset with high-quality annotations to advance the research in this field. We also propose an asymmetric contextual modulation module specially designed for detecting infrared small targets. To better highlight small targets, besides a top-down global contextual feedback, we supplement a bottom-up modulation pathway based on point-wise channel attention for exchanging high-level semantics and subtle low-level details. We report ablation studies and comparisons to state-of-the-art methods, where we find that our approach performs significantly better. Our dataset and code are available online 1 .
ISSN:2642-9381
DOI:10.1109/WACV48630.2021.00099