Zhang, Ying
Zhu, Kewen
Li, Zejian
Liu, Zhongni
Jia, Kaixin
Zhang, Jiesi
Sun, Lingyun
Funding for this research was provided by:
National Natural Science Foundation of China (Grant No. 62576306)
Youth Program of Humanities and Social Sciences of the Ministry of Education (Grant No.23YJCZH338)
Article History
Received: 3 May 2025
Accepted: 16 March 2026
First Online: 22 April 2026
Competing interests
: The authors declare no competing interests.
: This study was reviewed and approved by the Ethics Committee (Institutional Review Board, IRB) of Zhejiang University under approval number Zhejiang University Department of Psychology Ethics Application [2023] No. 022 on [March 10, 2023]. All procedures involving human participants were performed in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The approved research protocol covered the recruitment of novice restorers and experts, the experimental procedures comparing traditional and AI-assisted restoration workflows, and participant compensation, and approval was obtained prior to the commencement of data collection.
: Written informed consent was obtained from all participants prior to their participation in the study during the period from November 2024 to March 2025. The consent process was conducted by the research team, and consent was obtained directly from all adult participants. Prior to giving consent, participants were informed of the purpose of the study, the tasks involved, the voluntary nature of participation, their right to withdraw at any time without penalty, any potential risks and benefits, and the procedures for data collection, anonymisation, storage, and use for research and publication purposes. The consent covered participation in the study, the analysis of anonymised data, and the publication of findings in anonymised or aggregated form. No identifying personal information is reported in this article or included in the shared datasets.