Prompt Then Refine: Prompt-Free SAM-Enhanced Collaborative Learning Network for Detecting Salient Objects in Underwater Images

RGB-depth underwater salient object detection (USOD) poses considerable challenges, such as uneven lighting, visual interference, and image blur, which limit the effectiveness of traditional approaches. The segment anything model (SAM), known for its robust segmentation capabilities, offers a promising alternative. However, SAM depends on prompt labels (e.g., points, boxes, and masks) to perform effective resources typically unavailable in USOD datasets. To address this, we propose SAM-CLNet, a