Selective Attention-Based Network for Robust Infrared Small Target Detection
Infrared small target detection (IRSTD) plays a pivotal role in a broad spectrum of mission-critical applications, including maritime surveillance, military search and rescue, early warning systems, and precision-guided strikes, all of which demand the precise identification of dim, sub-pixel targets amid highly cluttered infrared backgrounds. Despite significant progress driven by deep learning methods, fundamental challenges persist: infrared small targets occupy extremely limited spatial extents (often only a few pixels), exhibit low signal-to-clutter ratios, and are easily confused with structurally complex backgrounds that frequently induce false alarms. Existing encoder-decoder arch...
| Authors | Yingming Zhang, Wuqi Su, Qing Xiao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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