  Wires and powerlines are common visual distractions that often undermine the
aesthetics of photographs. The manual process of precisely segmenting and
removing them is extremely tedious and may take up hours, especially on
high-resolution photos where wires may span the entire space. In this paper, we
present an automatic wire clean-up system that eases the process of wire
segmentation and removal/inpainting to within a few seconds. We observe several
unique challenges: wires are thin, lengthy, and sparse. These are rare
properties of subjects that common segmentation tasks cannot handle, especially
in high-resolution images. We thus propose a two-stage method that leverages
both global and local contexts to accurately segment wires in high-resolution
images efficiently, and a tile-based inpainting strategy to remove the wires
given our predicted segmentation masks. We also introduce the first wire
segmentation benchmark dataset, WireSegHR. Finally, we demonstrate
quantitatively and qualitatively that our wire clean-up system enables fully
automated wire removal with great generalization to various wire appearances.
