Abstract
Content-aware image completion or in-painting is a fundamental tool for the correction of defects or removal of
objects in images. We propose a non-parametric in-painting
algorithm that enforces both structural and aesthetic (style)
consistency within the resulting image. Our contributions
are two-fold: 1) we explicitly disentangle image structure
and style during patch search and selection to ensure a visually consistent look and feel within the target image. 2)
we perform adaptive stylization of patches to conform the
aesthetics of selected patches to the target image, so harmonizing the integration of selected patches into the final composition. We show that explicit consideration of visual style
during in-painting delivers excellent qualitative and quantitative results across the varied image styles and content,
over the Places2 scene photographic dataset and a challenging new in-painting dataset of artwork derived from BAM