Image generation models have made remarkable progress,and image evaluation is crucial for explaining and driving the development of these models.Previous studies have extensively explored human and automatic evaluatio...Image generation models have made remarkable progress,and image evaluation is crucial for explaining and driving the development of these models.Previous studies have extensively explored human and automatic evaluations of image generation.Herein,these studies are comprehensively surveyed,specifically for two main parts:evaluation protocols and evaluation methods.First,10 image generation tasks are summarized with focus on their differences in evaluation aspects.Based on this,a novel protocol is proposed to cover human and automatic evaluation aspects required for various image generation tasks.Second,the review of automatic evaluation methods in the past five years is highlighted.To our knowledge,this paper presents the first comprehensive summary of human evaluation,encompassing evaluation methods,tools,details,and data analysis methods.Finally,the challenges and potential directions for image generation evaluation are discussed.We hope that this survey will help researchers develop a systematic understanding of image generation evaluation,stay updated with the latest advancements in the field,and encourage further research.展开更多
基金supported by the National Natural Science Foundation of China(No.62006208)the Provincial Key Research and Development Plan of Zhejiang Province(No.2024C01250(SD2))。
文摘Image generation models have made remarkable progress,and image evaluation is crucial for explaining and driving the development of these models.Previous studies have extensively explored human and automatic evaluations of image generation.Herein,these studies are comprehensively surveyed,specifically for two main parts:evaluation protocols and evaluation methods.First,10 image generation tasks are summarized with focus on their differences in evaluation aspects.Based on this,a novel protocol is proposed to cover human and automatic evaluation aspects required for various image generation tasks.Second,the review of automatic evaluation methods in the past five years is highlighted.To our knowledge,this paper presents the first comprehensive summary of human evaluation,encompassing evaluation methods,tools,details,and data analysis methods.Finally,the challenges and potential directions for image generation evaluation are discussed.We hope that this survey will help researchers develop a systematic understanding of image generation evaluation,stay updated with the latest advancements in the field,and encourage further research.
