English(EN) Uncertainty-Guided Adverse Weather Restoration via Gated Transformer Network

新型 AI 网络增强恶劣天气下的图像恢复效果

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-03 04:00

研究人员开发了一个名为不确定性引导恶劣天气恢复网络 (UAR-Net) 的新框架，以改善恶劣天气条件下的图像恢复效果。该 AiO 框架利用门控 Transformer 和平衡多尺度跳跃连接来更好地处理异构退化。该网络包含一个不确定性感知细化头，用于去除伪影和增强细节，并使用亮度感知能量损失进行训练，以确保准确重建和校准良好的不确定性。 AI

影响这项研究可能为需要在恶劣天气条件下获得清晰图像的应用带来更强大的图像处理工具。

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arXiv cs.CV TIER_1 English(EN) · Zheke Jin, Yuning Cui, Tianle Jin, Alois Knoll, Hu Cao · 2026-09-03 04:00

通过门控Transformer网络进行不确定性引导的恶劣天气恢复

arXiv:2609.02434v1 Announce Type: new Abstract: Restoring images degraded by adverse weather remains challenging due to spatially heterogeneous degradations. Many existing weather-specific restoration models rely on weather-agnostic global aggregation, naive cross-scale fusion, a…

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通过门控Transformer网络进行不确定性引导的恶劣天气恢复

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