Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains

arXiv:2404.12091v1 Announce Type: new
Abstract: Recent advances in image deraining have focused on training powerful models on mixed multiple datasets comprising diverse rain types and backgrounds. However, this approach tends to overlook the inherent differences among rainy images, leading to suboptimal results. To overcome this limitation, we focus on addressing various rainy images by delving into meaningful representations that encapsulate both the rain and background components. Leveraging these representations as instructive guidance, we put forth a Context-based Instance-level Modulation (CoI-M) …

abstract advances arxiv cs.cv datasets differences diverse focus however image images mixed multiple rain results training type types