Research on the Construction and Reproduction of Traditional Peony Patterns in Yaozhou Celadon Based on Generative Artificial Intelligence

QIN Song; LIU Baojun; BAI Xiaobo; LIU Junling

doi:10.19554/j.cnki.1001-3563.2025.18.034

PDF(15375 KB)

Packaging Engineering ›› 2025, Vol. 46 ›› Issue (18) : 380-389. DOI: 10.19554/j.cnki.1001-3563.2025.18.034

Research on the Construction and Reproduction of Traditional Peony Patterns in Yaozhou Celadon Based on Generative Artificial Intelligence

QIN Song¹, LIU Baojun¹, BAI Xiaobo¹, LIU Junling^2,*

Author information +

History +

Abstract

Exploring a Workflow and Design Approach for Expanding Traditional Peony Patterns in Yaozhou Celadon Using Generative Artificial Intelligence.This study focuses on the traditional peony patterns found in Yaozhou celadon as the research object. By establishing a multi-model combination process, we aim to organize the data, anchor labels, train and optimize the models, and leverage generative artificial intelligence techniques to develop an intelligent method for generating peony patterns with a specific style. This endeavor seeks to broaden the sample base of traditional peony patterns in Yaozhou celadon, providing designers with a vast array of materials for re-creation. The experimental results demonstrate that by adopting the LoRA model training method, the characteristic features of traditional peony patterns in Yaozhou celadon can be reproduced in Stable Diffusion with only a small number of samples. In the context of rapid development of digital intelligence, this approach not only meets the needs of the new era and independent intellectual property rights, but also provides a good reference and method for the digital inheritance of other historical kilns in China.

Key words

Artificial Intelligence Generated Content (AIGC) / Traditional Peony Patterns in Yaozhou Celadon / Low- Rank Adaptation of Large Language Models (LoRA) / Stable Diffusion

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

QIN Song, LIU Baojun, BAI Xiaobo, LIU Junling. Research on the Construction and Reproduction of Traditional Peony Patterns in Yaozhou Celadon Based on Generative Artificial Intelligence[J]. Packaging Engineering. 2025, 46(18): 380-389 https://doi.org/10.19554/j.cnki.1001-3563.2025.18.034

References

[1] 高黎, 王思茜. 耀州窑刻划花装饰综述[J]. 中国陶瓷, 2021, 57(10): 101-109.
GAO L, WANG S Q.Summary of Carved Flower Decoration in Yaozhou Kiln[J]. China Ceramics, 2021, 57(10): 101-109.
[2] 陈鋆纯, 彭坚, 郭寅曼, 等. 基于花瑶挑花纹样风格化图像的辅助设计研究[J]. 包装工程, 2022, 43(14): 246-253.
CHEN J C, PENG J C, GUO Y M, et al.Computer-aided Design Based on Stylized Images of Huayao Cross- stitch Patterns[J]. Packaging Engineering, 2022, 43(14): 246-253.
[3] 乔锦浩, 肖懿, 崔誉丹, 等. 特定风格剪纸艺术的智能生成[J]. 包装工程, 2021, 42(14): 74-80.
QIAO J H, XIAO Y, CUI Y D, et al.Intelligent Generation for Specific Style of Paper-Cutting Art[J]. Packaging Engineering, 2021, 42(14): 74-80.
[4] BELHI A, BOURAS S, FOU F.Digitization and Preservation of Cultural Heritage: The CEPROQHA Approach[C]//Proceedings of the 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Malabe: SKIMA, 2017: 1-7.
[5] 侯云鹏, 彭涵, 刘育晖. 基于LoRA模型的非遗数字化传承:以楚漆器为例[J]. 设计艺术研究, 2024, 14(1): 14-18.
HOU Y P, PENG H, LIU Y H.Digital Inheritance of Intangible Cultural Heritage Based on the LoRA Model: a Case Study of Chu Lacquerware[J]. Desgin Research, 2024, 14(1): 14-18.
[6] 于鹏, 张毅. 从特征辨识到图像生成: 基于AIGC范式的苗族服饰设计[J]. 丝绸, 2024, 61(3): 1-10.
YU P, ZHANG Y.From Feature Recognition to Image Generation: Miao Ethnic Costume Design Based on the AIGC Paradigm[J]. Journal of Silk, 2024, 61(3): 1-10.
[7] 舒畇溦, 孟凯宁, 孙宁. 彝族传统纹样的数字化传承与重塑设计研究[J]. 吉林艺术学院学报, 2023(4): 11-17.
SHU Y W, MENG K N, SUN N.Research on Digital Inheritance and Redesign of Yi Ethnic Traditional Patterns[J]. Journal of Jilin University of Arts, 2023(4): 11-17.
[8] ZHANG H.Combined Development of Artificial Intelligence and Art Design[C]//2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP). Xi'an: ICSP, 2021: 1023-1026.
[9] 冯金牛, 周强, 张瑞瑞, 等. 基于卷积神经网络的中国古陶瓷智能断代研究[J]. 陶瓷学报, 2022, 43(1): 145-152.
FENG J N, ZHOU Q, ZHANG R R, et al.Intelligent Dating of Chinese Ancient Ceramics Based on Convolutional Neural Network[J]. Journal of Ceramics, 2022, 43(1): 145-152.
[10] 崔因, 杨建明, 李芳, 等. 磁州窑装饰纹样智能辅助设计研究[J].包装工程, 2023, 44(16): 1-9.
CUI Y, YANG J M, LI F, et al.AI-assisted Design for Decorative Pattern of Cizhou Kiln[J]. Packaging Engineering, 2023, 44(16): 1-9
[11] HAN X R, LIU Y Y, ZHANG H W, et al.Pattern Derivative Design of Black Copper Infused with Silver Using AI-based Pattern Generation and Image Style Transfer Algorithm[C]//2023 International Conference on Artificial Intelligence and Automation Control (AIAC). Xiamen: AIAC, 2023: 177-181.
[12] 覃京燕, 贾冉. 人工智能在非物质文化遗产中的创新设计研究: 以景泰蓝为例[J]. 包装工程, 2020, 41(06): 1-6.
QIN J Y, JIA R.Innovative Designof Artificial Intelligence in Intangible Cultural Heritage: Take Cloisonné as an Example[J]. Packaging Engineering, 2020, 41(6): 1-6.
[13] 张海龙, 黄文锋, 路翔, 等. 知识增强大模型在信息系统故障分析中的应用研究[J].现代计算机, 2024, 30(6): 87-93.
ZHANG H L, HUANG W F, LU X, et al.Research on the Application of Knowledge-Enhanced Large Models in Information System Fault Analysis[J]. Modern Computer, 2024,30(6): 87-93.
[14] 曾建勇, 沈晓萍. 基于Stable Diffusion的虚拟人形象预设计的应用与研究[J]. 现代信息科技, 2024, 8(3): 169-175.
ZENG J Y, SHEN X P.Application and Research on Virtual Human Image Pre-design Based on Stable Diffusion[J]. Modern Information Technology, 2024, 8(3): 169-175
[15] 孙贾康. 宋代耀州窑牡丹纹饰研究[J]. 陶瓷, 2023(12): 50-52.
SUN J K.Study on Peony Oranmentation of YaoZhou Kiln in Song Dynasty[J]. Ceramics, 2023(12): 50-52.