UIU-Net: U-Net in U-Net for Infrared Small Object Detection

Learning-based infrared small object detection methods currently rely heavily on the classification backbone network. The proposed UIU-Net also produces powerful generalization performance for video sequence infrared small object datasets, e.g., ATR ground/air video sequence dataset.

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• 1 This tends to result in tiny object loss and feature distinguishability limitations as the network depth increases.
• 2 Additionally, small objects in infrared images are frequently emerged bright and dark, posing severe demands for obtaining precise object contrast information.
• 3 For this reason, we in this paper propose a simple and effective "U-Net in U-Net" framework, UIU-Net for short, and detect small objects in infrared images.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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