English(EN) DORIS: Polarization Aware Multimodal Degradation Perception for Underwater Image Restoration

DORIS框架利用偏振和RGB信息实现更好的水下图像恢复

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-11 05:00

研究人员推出DORIS，一个新颖的框架，旨在通过联合利用偏振和RGB信息来增强水下图像恢复。这种多模态方法旨在改善对混合水下退化的理解和表示，从而实现更鲁棒的图像恢复。为了支持这项研究，创建了一个名为MixPolar的新基准，其中包括带有相应注释的真实水下图像，用于评估退化感知、图像恢复和下游任务性能。 AI

影响这项研究可能带来改进的水下成像能力，用于探索和科学分析。

排序理由该集群描述了在arXiv上发布的一篇新研究论文和基准测试。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Wenshuo Zhang, Xiangyue Zhang, Junlin Li, Wenjie Tian, Yubo Zheng, Zhixin Dong, Hongli Xu, Jingyu Ru, Xinde Li · 2026-11-11 05:00

DORIS：水下图像恢复的偏振感知多模态退化感知

arXiv:2610.17991v2 Announce Type: replace Abstract: Recovering high-quality images from degraded underwater observations is crucial for underwater exploration. Polarization observations show promise as an effective source of complementary physical cues for recovering target radia…

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报道来源 [1]

DORIS：水下图像恢复的偏振感知多模态退化感知

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