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In contrast, we learn hypothesis search in a principled fashion that lets us optimize an arbitrary task loss during training, leading to large improvements on classic computer vision tasks.
Our method reverses this process: we propose a set of horizon line candidates and score each based on the vanishing points it contains.
#2 best model for Horizon Line Estimation on York Urban Dataset
The horizon line is an important contextual attribute for a wide variety of image understanding tasks.
#2 best model for Horizon Line Estimation on Horizon Lines in the Wild (using extra training data)
We present a novel approach for vanishing point detection from uncalibrated monocular images.
#3 best model for Horizon Line Estimation on York Urban Dataset
We show that, in images of man-made environments, the horizon line can usually be hypothesized based on an a contrario detection of second-order grouping events.