( Image credit: Densely Connected Pyramid Dehazing Network )
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Due to the lack of natural scene and haze prior information, it is greatly challenging to completely remove the haze from single image without distorting its visual content.
The recent physical model-free dehazing methods have achieved state-of-the-art performances.
To alleviate the intra-domain gap of the synthetic domain, we propose an intra-domain adaptation to align distributions of other subsets to the optimal subset by adversarial learning.
However, for images taken in real-world, the illumination is not uniformly distributed over whole image which brings model mismatch and possibly results in color shift of the deep models using ASM.