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论文类型：会议论文

发表时间：2021-03-05

关键字：Self-adaptive Rain Removal; Flexible Rain Model; Attention Mechanism

摘要：Visual quality degradation by rain streaks in images/videos is a significant factor that makes many computer vision systems fail to function properly. However, existing rain removal methods tend to remove a specific type of rain streaks while cannot deal with diverse real rainy images. In this paper, we formulate a novel rain model collectively with two contrasting rain streaks and a weighting map. To self-adaptively handle the rain removal problem in the presence of various types of rain streaks, we further propose a bilevel optimization learning framework. Then, we synthesize a new dataset to evaluate the ability of our method to deal with diverse rain streaks. Extensive experiments show that our method can make better performance on both synthesized and real rainy images.