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.
A pixel distribution remapping and multi- prior retinex variational model for underwater image en- hancement.IEEE Transactions on Multimedia, 26:7838– 7849, 2024
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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.