Residual-Conditioned Optimal Transport: Towards Structure-preserving Unpaired and Paired Image Restoration

arXiv:2405.02843v1 Announce Type: new
Abstract: Deep learning-based image restoration methods have achieved promising performance. However, how to faithfully preserve the structure of the original image remains challenging. To address this challenge, we propose a novel Residual-Conditioned Optimal Transport (RCOT) approach, which models the image restoration as an optimal transport (OT) problem for both unpaired and paired settings, integrating the transport residual as a unique degradation-specific cue for both the transport cost and the transport map. Specifically, we first formalize a …

abstract arxiv challenge cs.cv deep learning however image image restoration novel performance residual restoration transport type