The lack of a holistic evaluation framework for image generation models has hindered advancements in assessing their technological and societal impacts, such as bias and fairness.
Our research addresses the critical need for comprehensive assessment in image generation by evaluating models across 12 pivotal dimensions, fostering deeper insights into their performance variations.
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