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Prompt and Refinement: Asymmetric Mutual Learning for Infrared Small Target Detection with Noisy Labels
Existing data-driven infrared small target detection (ISTD) methods typically require large-scale datasets with accurate pixel-level annotations for model training. However, such labor-intensive requirements are difficult to satisfy in real-world applications due to the heavy reliance on expert know
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