UniV2D is a dual-branch network that lets high-level saliency masks guide low-level image restoration and lets restored features improve saliency detection, outperforming prior separate-stage methods on underwater benchmarks.
Diving into underwater: Segment anything model guided underwater salient instance segmentation and a large-scale dataset
2 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
LUSIS-DETR with AquaBSAM reports leading performance on four underwater instance segmentation datasets and real-time FP16 inference on an NVIDIA T4 GPU.
citing papers explorer
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UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection
UniV2D is a dual-branch network that lets high-level saliency masks guide low-level image restoration and lets restored features improve saliency detection, outperforming prior separate-stage methods on underwater benchmarks.
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Aqua Boundary-Saliency Attention Module for Lightweight Underwater Salient Instance Segmentation Detection Transformer
LUSIS-DETR with AquaBSAM reports leading performance on four underwater instance segmentation datasets and real-time FP16 inference on an NVIDIA T4 GPU.