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Found 2 papers, 1 papers with code
Learning Heavily-Degraded Prior for Underwater Object Detection
Therefore, we propose a residual feature transference module (RFTM) to learn a mapping between deep representations of the heavily degraded patches of DFUI- and underwater- images, and make the mapping as a heavily degraded prior (HDP) for underwater detection.
Joint Perceptual Learning for Enhancement and Object Detection in Underwater Scenarios
Based on these factual opinions, we propose a bilevel optimization formulation for jointly learning underwater object detection and image enhancement, and then unroll to a dual perception network (DPNet) for the two tasks.
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