Assessing Image Quality Using a Simple Generative Representation

arXiv:2404.18178v1 Announce Type: cross
Abstract: Perceptual image quality assessment (IQA) is the task of predicting the visual quality of an image as perceived by a human observer. Current state-of-the-art techniques are based on deep representations trained in discriminative manner. Such representations may ignore visually important features, if they are not predictive of class labels. Recent generative models successfully learn low-dimensional representations using auto-encoding and have been argued to preserve better visual features. Here we leverage existing auto-encoders and propose VAE-QA, …

abstract art arxiv assessment cs.ai cs.cv cs.gr cs.lg current eess.iv features generative human image predictive quality representation simple state type visual