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Nian Wang

2 accepted papers

2025

Exploiting Diffusion Prior for Real-World Image Dehazing with Unpaired Training

AAAI 2025technical

Unpaired training has been verified as one of the most effective paradigms for real scene dehazing by learning from unpaired real-world hazy and clear images. Although numerous studies have been proposed, current methods demonstrate limited generalization for various real scenes due to limited featu…

2025

When Schrodinger Bridge Meets Real-World Image Dehazing with Unpaired Training

ICCV 2025poster

Recent advancements in unpaired dehazing, particularly those using GANs, show promising performance in processing real-world hazy images. However, these methods tend to face limitations due to the generator's limited transport mapping capability, which hinders the full exploitation of their effectiv…

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