Shadow Removal via Cascade Large Mask Inpainting

Juwan Kim, Seung-Heon Kim, I. Jang
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Abstract

We present a novel shadow removal framework based on the image inpainting approach. The proposed method consists of two cascade Large-Mask inpainting(LaMa) networks for shadow inpainting and edge inpainting. Experiments with the ISTD and adjusted ISTD dataset show that our method achieves competitive shadow removal results compared to state-of-the methods. And we also show that shadows are well removed from complex and large shadow images, such as urban aerial images
阴影去除通过级联大面具油漆
提出了一种基于图像补色方法的阴影去除框架。该方法由两个级联的大掩模网络组成,分别用于阴影和边缘的绘制。在ISTD和调整后的ISTD数据集上进行的实验表明,与现有方法相比,我们的方法取得了具有竞争力的阴影去除效果。我们还表明,阴影可以很好地从复杂的大阴影图像中去除,比如城市航空图像
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