SANet: Selective Attention Network for Infrared Small Target Detection

Key points

• Infrared small target detection aims to accurately identify and locate dim targets in complex backgrounds and supports applications such as maritime surveillance and military search and rescue.1
• Spatial and channel attention further refine the features and improve target-background discrimination.1
• To address the limitations of static skip connections in U-Net, a selective attention fusion module adaptively integrates features across scales using spatially varying weights.1
• Experiments on three public benchmarks, NUAA-SIRST, IRSTD-1K, and NUDT-SIRST, show that SANet achieves competitive performance in intersection over union (IoU), normalized IoU, detection probability, and false alarm rate.1

Sources (1)

• [1]SANet: Selective Attention Network for Infrared Small Target Detection
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 11:34 AM

  This paper proposes a selective attention network (SANet) for infrared small target detection.

  Infrared small target detection aims to accurately identify and locate dim targets in complex backgrounds and supports applications such as maritime surveillance and military search and rescue.

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