Learning Spatially Adaptive Structural Coordination for Underwater Salient Object Detection
Underwater salient object detection (USOD) has attracted increasing attention for underwater scene understanding and vision-guided robotic applications. However, the spatially non-uniform degradation in underwater images causes spatially varying reliability of structural cues: boundary-sensitive responses can enhance object contours but are vulnerable to degradation-induced noise, whereas region-coherent responses improve semantic completeness but may blur object boundaries. Existing methods rarely explicitly consider the spatial variation in structural cue reliability under underwater image degradation. To address this problem, this work proposes SASC-USOD, a novel framework for learning...
| Authors | Lin Hong, Chenhui Wang, Linan Deng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 May 2026 |
| Last updated at source | 22 August 2026 |
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