Evaluating Text to Image Synthesis: Survey and Taxonomy of Image Quality Metrics

arXiv:2403.11821v1 Announce Type: new
Abstract: Recent advances in text-to-image synthesis have been enabled by exploiting a combination of language and vision through foundation models. These models are pre-trained on tremendous amounts of text-image pairs sourced from the World Wide Web or other large-scale databases. As the demand for high-quality image generation shifts towards ensuring content alignment between text and image, novel evaluation metrics have been developed with the aim of mimicking human judgments. Thus, researchers have started to collect datasets …

abstract advances arxiv combination cs.ai cs.cv cs.gr databases demand foundation image language metrics quality scale survey synthesis taxonomy text text-image text-to-image through type vision web world world wide web