论文标题

红外小目标检测的不对称上下文调制

Asymmetric Contextual Modulation for Infrared Small Target Detection

论文作者

Dai, Yimian, Wu, Yiquan, Zhou, Fei, Barnard, Kobus

论文摘要

单框红外的小目标检测仍然是一个挑战,这不仅是由于固有目标特征缺乏,而且由于缺乏公共数据集。在本文中,我们首先为开放数据集提供了具有高质量注释的开放数据集,以推进该领域的研究。我们还提出了一个不对称上下文调制模块,专门设计用于检测红外小目标。为了更好地强调小目标,除了自上而下的全球上下文反馈外,我们还基于关注点渠道的关注来补充自下而上的调制途径,以交换高级语义和微妙的低级详细信息。我们报告了与最先进方法的消融研究和比较,我们发现我们的方法的表现明显更好。我们的数据集和代码可在线提供。

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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