Abstract
Many images shared over the web include overlaid objects, or visual motifs, such as text, symbols or drawings,
which add a description or decoration to the image. For
example, decorative text that specifies where the image was
taken, repeatedly appears across a variety of different images. Often, the reoccurring visual motif, is semantically
similar, yet, differs in location, style and content (e.g., text
placement, font and letters). This work proposes a deep
learning based technique for blind removal of such objects.
In the blind setting, the location and exact geometry of the
motif are unknown. Our approach simultaneously estimates
which pixels contain the visual motif, and synthesizes the
underlying latent image. It is applied to a single input image, without any user assistance in specifying the location
of the motif, achieving state-of-the-art results for blind removal of both opaque and semi-transparent visual motifs.