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Hauptverfasser: Cao, Yu, Duan, Xin, Meng, Xiangqiao, Mok, P. Y., Li, Ping, Lee, Tong-Yee
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2410.02288
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author Cao, Yu
Duan, Xin
Meng, Xiangqiao
Mok, P. Y.
Li, Ping
Lee, Tong-Yee
author_facet Cao, Yu
Duan, Xin
Meng, Xiangqiao
Mok, P. Y.
Li, Ping
Lee, Tong-Yee
contents This paper reviews published research in the field of computer-aided colorization technology. We argue that the colorization task originates from computer graphics, prospers by introducing computer vision, and tends to the fusion of vision and graphics, so we put forward our taxonomy and organize the whole paper chronologically. We extend the existing reconstruction-based colorization evaluation techniques, considering that aesthetic assessment of colored images should be introduced to ensure that colorization satisfies human visual-related requirements and emotions more closely. We perform the colorization aesthetic assessment on seven representative unconditional colorization models and discuss the difference between our assessment and the existing reconstruction-based metrics. Finally, this paper identifies unresolved issues and proposes fruitful areas for future research and development. Access to the project associated with this survey can be obtained at https://github.com/DanielCho-HK/Colorization.
format Preprint
id arxiv_https___arxiv_org_abs_2410_02288
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Computer-aided Colorization State-of-the-science: A Survey
Cao, Yu
Duan, Xin
Meng, Xiangqiao
Mok, P. Y.
Li, Ping
Lee, Tong-Yee
Computer Vision and Pattern Recognition
This paper reviews published research in the field of computer-aided colorization technology. We argue that the colorization task originates from computer graphics, prospers by introducing computer vision, and tends to the fusion of vision and graphics, so we put forward our taxonomy and organize the whole paper chronologically. We extend the existing reconstruction-based colorization evaluation techniques, considering that aesthetic assessment of colored images should be introduced to ensure that colorization satisfies human visual-related requirements and emotions more closely. We perform the colorization aesthetic assessment on seven representative unconditional colorization models and discuss the difference between our assessment and the existing reconstruction-based metrics. Finally, this paper identifies unresolved issues and proposes fruitful areas for future research and development. Access to the project associated with this survey can be obtained at https://github.com/DanielCho-HK/Colorization.
title Computer-aided Colorization State-of-the-science: A Survey
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2410.02288