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ADGNet: Asymmetric Dual-text Guided Network for Infrared Small Target Detection

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

InfRared Small Target Detection (IRSTD) is a challenging task. Relying solely on pixel-level information, vision-only methods struggle to distinguish targets from clutter. Current multimodal methods typically describe both targets and backgrounds with a single textual prompt. Such an approach lacks dedicated regional guidance and ignores infrared semantic asymmetry. Consequently, it provides insufficient background suppression information and introduces severe feature optimization conflicts, overwhelming small targets with noise. To address these issues, we propose a novel Asymmetric Dual-text

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Evidence & attribution

First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.