Uncovering the Over-smoothing Challenge in Image Super-Resolution: Entropy-based Quantification and Contrastive Optimization

arXiv:2201.01034v2 Announce Type: replace-cross
Abstract: PSNR-oriented models are a critical class of super-resolution models with applications across various fields. However, these models tend to generate over-smoothed images, a problem that has been analyzed previously from the perspectives of models or loss functions, but without taking into account the impact of data properties. In this paper, we present a novel phenomenon that we term the center-oriented optimization (COO) problem, where a model's output converges towards the center point of similar high-resolution …

abstract applications arxiv challenge class cs.cv eess.iv entropy fields functions generate however image images loss optimization perspectives quantification type