Detecting Road Obstacles by Erasing Them

Vehicles can encounter a myriad of obstacles on the road, and it is not feasible to record them all beforehand to train a detector. Our method selects image patches and inpaints them with the surrounding road texture, which tends to remove obstacles from those patches. It them uses a network trained to recognize discrepancies between the original patch and the inpainted one, which signals an erased obstacle. We also contribute a new dataset for monocular road obstacle detection, and show that our approach outperforms the state-of-the-art methods on both our new dataset and the standard Fishyscapes Lost & Found benchmark.