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Plug-and-Play global and local collaborative fusion for weakly supervised object detection
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DOI：10.1016/j.knosys.2026.115857.png)
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Abstract
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• We propose a plug-and-play global and local collaborative fusion method to improve the performance of weakly supervised object detection. • We design a pixel-level global information awareness module that utilizes singular value decomposition for image reconstruction. • We propose a local detail fusion module to enable the visual encoder to learn detailed information about target objects. • We demonstrate the effectiveness and superiority of our plug-and-play method through extensive experiments.
Keywords:
Weakly supervised object detection
Multi-instance learning
Low-rank approximation
Global and local fusion
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