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Image generation evaluation: a comprehensive survey of human and automatic evaluations
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Qi LIU1, Shuanglin YANG2, Zejian LI1, Lefan HOU3, Chenye MENG3,Ying ZHANG1, Lingyun SUN3. Image generation evaluation: a comprehensive survey of human and automatic evaluations[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .
@article{title="Image generation evaluation: a comprehensive survey of human and automatic evaluations",
author="Qi LIU1, Shuanglin YANG2, Zejian LI1, Lefan HOU3, Chenye MENG3,Ying ZHANG1, Lingyun SUN3",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2400904"
}
%0 Journal Article
%T Image generation evaluation: a comprehensive survey of human and automatic evaluations
%A Qi LIU1
%A Shuanglin YANG2
%A Zejian LI1
%A Lefan HOU3
%A Chenye MENG3
%A Ying ZHANG1
%A Lingyun SUN3
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%P
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2400904
TY - JOUR
T1 - Image generation evaluation: a comprehensive survey of human and automatic evaluations
A1 - Qi LIU1
A1 - Shuanglin YANG2
A1 - Zejian LI1
A1 - Lefan HOU3
A1 - Chenye MENG3
A1 - Ying ZHANG1
A1 - Lingyun SUN3
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2400904
Abstract: 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 by focusing 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, this the challenges and potential directions for image generation evaluation are discussed. We hope that this survey will help researchers to develop a systematic understanding of image generation evaluation, stay updated with the latest advancements in the field, and encourage further research.
Open peer comments: Debate/Discuss/Question/Opinion
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