Image inpainting is a challenging problem as it needs to fill the information
of the corrupted regions. Most of the existing inpainting algorithms assume
that the positions of the corrupted regions are known. Different from the
existing methods that usually make some assumptions on the corrupted regions,
we present an efficient blind image inpainting algorithm to directly restore a
clear image from a corrupted input. Our algorithm is motivated by the residual
learning algorithm which aims to learn the missing infor- mation in corrupted
regions. However, directly using exist- ing residual learning algorithms in
image restoration does not well solve this problem as little information is
available in the corrupted regions. To solve this problem, we introduce an
encoder and decoder architecture to capture more useful information and develop
a robust loss function to deal with outliers. Our algorithm can predict the
missing information in the corrupted regions, thus facilitating the clear image
restoration. Both qualitative and quantitative experimental demonstrate that
our algorithm can deal with the corrupted regions of arbitrary shapes and
performs favorably against state-of-the-art methods.

提出了一种盲图像修复算法，通过利用残差学习与编码解码结构来恢复缺失信息，以处理任意形状的损坏区域。