IRConStyle: Image Restoration Framework Using Contrastive Learning and Style Transfer

arXiv:2402.15784v1 Announce Type: new
Abstract: Recently, the contrastive learning paradigm has achieved remarkable success in high-level tasks such as classification, detection, and segmentation. However, contrastive learning applied in low-level tasks, like image restoration, is limited, and its effectiveness is uncertain. This raises a question: Why does the contrastive learning paradigm not yield satisfactory results in image restoration? In this paper, we conduct in-depth analyses and propose three guidelines to address the above question. In addition, inspired by style transfer and …

abstract arxiv classification cs.cv detection framework image image restoration low paradigm question raises segmentation style style transfer success tasks transfer type uncertain