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README.md
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As a result, PGL-Net achieves superior restoration quality comparable to heavy Transformer models, but with only ~3% of the parameters.
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- **Paper:** [Efficient Real-World Dehazing via Physics-Inspired Global-Local Decoupling](https://arxiv.org/abs/2606.25732)[Code](https://github.com/sc-30-bit/PGL-Net)
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- **Task:** Real-World Image Dehazing
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- **Model Variants:** PGL-Net-T (Tiny), PGL-Net-S (Small)
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As a result, PGL-Net achieves superior restoration quality comparable to heavy Transformer models, but with only ~3% of the parameters.
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- **Paper:** [Efficient Real-World Dehazing via Physics-Inspired Global-Local Decoupling](https://arxiv.org/abs/2606.25732) [[Code]](https://github.com/sc-30-bit/PGL-Net)
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- **Task:** Real-World Image Dehazing
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- **Model Variants:** PGL-Net-T (Tiny), PGL-Net-S (Small)
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