FlashEval: Towards Fast and Accurate Evaluation of Text-to-image Diffusion Generative Models

arXiv:2403.16379v1 Announce Type: new
Abstract: In recent years, there has been significant progress in the development of text-to-image generative models. Evaluating the quality of the generative models is one essential step in the development process. Unfortunately, the evaluation process could consume a significant amount of computational resources, making the required periodic evaluation of model performance (e.g., monitoring training progress) impractical. Therefore, we seek to improve the evaluation efficiency by selecting the representative subset of the text-image dataset. We systematically investigate …

arxiv cs.cv diffusion evaluation generative generative models image image diffusion text text-to-image type