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- W4312461657 abstract "Demoiréing is a multi-level image restoration task involving texture and color restoration. However, the moiré pattern in documents is difficult to remove, and the blurred font also appears. In this paper, we propose a multi-scale coarse-to-fine neural network to solve this problem. First, a multi-scale dense network structure is adopted to capture the moiré pattern from different resolution features, in which a spatial attention module is utilized that has remarkable performance in capturing moiré pattern. Second, a lightweight deblurring network is taken to remove the blur in documents for further optimziation. Through ablation experiments, the effectiveness of our method is demonstrated. The network proposed in this paper takes the third place in the document demoiréing track of the 2022 Baidu.com AI Competition." @default.
- W4312461657 created "2023-01-04" @default.
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- W4312461657 date "2022-01-01" @default.
- W4312461657 modified "2023-09-26" @default.
- W4312461657 title "Multi-scale Coarse-to-Fine Network for Demoiréing" @default.
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- W4312461657 doi "https://doi.org/10.1007/978-3-031-18916-6_19" @default.
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