The horizon line is an important property for a wide variety of image understanding tasks. As such, many methods have been introduced to estimate the horizon line from a single image, primarily geometric methods which assume the presence of specific cues in the scene (e.g., vanishing points). These purely geometric methods are limited in their real-world capability, require extensive tuning, and are tested on benchmark datasets designed to showcase their ability. We introduce a large, realistic evaluation dataset, Horizon Lines in the Wild (HLW), containing natural images with labeled horizon lines.
Workman et al. REF goes further and directly estimates the horizon line in the single image.
Horizon Lines in the Wild
ArXiv
ArXiv
Computer Science