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In this paper, in order to get a better understanding of the human visualpreferences for AIGIs, a large-scale IQA database for AIGC is established,which is named as AIGCIQA2023. We first generate over 2000 images based on 6state-of-the-art text-to-image generation models using 100 prompts. Based onthese images, a well-organized subjective experiment is conducted to assess thehuman visual preferences for each image from three perspectives includingquality, authenticity and correspondence. Finally, based on this large-scaledatabase, we conduct a benchmark experiment to evaluate the performance ofseveral state-of-the-art IQA metrics on our constructed database.

AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI  Generated Images: from the Perspectives of Quality, Authenticity and  Correspondence