Joint Quality Assessment and Example-Guided Image Processing by Disentangling Picture Appearance from Content

arXiv:2404.13484v1 Announce Type: cross
Abstract: The deep learning revolution has strongly impacted low-level image processing tasks such as style/domain transfer, enhancement/restoration, and visual quality assessments. Despite often being treated separately, the aforementioned tasks share a common theme of understanding, editing, or enhancing the appearance of input images without modifying the underlying content. We leverage this observation to develop a novel disentangled representation learning method that decomposes inputs into content and appearance features. The model is trained in a self-supervised manner …

abstract arxiv assessment cs.cv deep learning domain editing eess.iv example image image processing images low processing quality restoration style tasks transfer type understanding visual