Asymmetric Contextual Modulation for Infrared Small Target Detection

• URL: http://arxiv.org/abs/2009.14530v1
• Date: Wed, 30 Sep 2020 09:30:08 GMT
• Title: Asymmetric Contextual Modulation for Infrared Small Target Detection
• Authors: Yimian Dai and Yiquan Wu and Fei Zhou and Kobus Barnard
• Abstract summary: This paper contributes 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.
• Score: 7.398907942239465
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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