“The cost volume, capturing the similarity of possible correspondences across two input images, is a key ingredient in state-of-the-art optical flow approaches. When sampling correspondences to build the cost volume, a large neighborhood radius is required to deal with large displacements, introducing a significant computational burden. To address this, coarse-to-fine or recurrent processing of the cost volume is usually adopted. … In this paper, we propose an alternative by constructing cost volumes with different dilation factors to capture small and large displacements simultaneously.”

Read the paper and see the full list of authors in IEEE Xplore.