  This paper describes and provides an initial solution to a novel video
editing task, i.e., video de-fencing. It targets automatic restoration of the
video clips that are corrupted by fence-like occlusions during capture. Our key
observation lies in the visual parallax between fences and background scenes,
which is caused by the fact that the former are typically closer to the camera.
Unlike in traditional image inpainting, fence-occluded pixels in the videos
tend to appear later in the temporal dimension and are therefore recoverable
via optimized pixel selection from relevant frames. To eventually produce
fence-free videos, major challenges include cross-frame sub-pixel image
alignment under diverse scene depth, and "correct" pixel selection that is
robust to dominating fence pixels. Several novel tools are developed in this
paper, including soft fence detection, weighted truncated optical flow method
and robust temporal median filter. The proposed algorithm is validated on
several real-world video clips with fences.
