Parallax Refinement Network Based on Adaptive Convolution

Abstract

To improve the accuracy of disparity refinement, this paper proposes a disparity refinement and sampling method based on adaptive convolution. The refine hypothesis is used to introduce other available information for disparity refinement, and different information is attached at different stages to augment the refine hypothesis. Based on the adaptive propagation method, the local cost volume is constructed and the aggregation operation is converted from the spatial domain to the disparity domain to alleviate the boundary blur problem caused by using large convolution windows and augmented the aggregation effect in texture-free or weakly textured areas. At the same