Establishing dense correspondences across semantically similar images is a challenging task, due to the large intra-class variation caused by unconstrained setting of images, which prone cause matching errors. To suppress potential ambiguity, NCNet explores neighborhood consensus pattern in 4D space all possible correspondences, based on assumption that correspondence continuous space. We retai...