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Multi-scale global-local collaborative learning for accurate significant object detection
Abstract Salient Object Detection (SOD) remains a fundamental task in computer vision and visual computing, supporting applications ranging from image understanding to human-computer interaction. Existing methods still face two coupled challenges: insufficient modeling of multi-scale salient structures and imbalanced fusion between global semantic information and local details, which often lead to incomplete salient regions and blurred boundaries.
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