HarmonyCut: Supporting Creative Chinese Paper-cutting Design with Form and Connotation Harmony
Huanchen Wang, Tianrun Qiu, Jiaping Li, Zhicong Lu, Yuxin Ma
摘要
Chinese paper-cutting, an Intangible Cultural Heritage (ICH), faces challenges from the erosion of traditional culture due to the prevalence of realism alongside limited public access to cultural elements. While generative AI can enhance paper-cutting design with its extensive knowledge base and efficient production capabilities, it often struggles to align content with cultural meaning due to users' and models' lack of comprehensive paper-cutting knowledge. To address these issues, we conducted a formative study (N=7) to identify the workflow and design space, including four core factors (Function, Subject Matter, Style, and Method of Expression) and a key element (Pattern). We then developed HarmonyCut, a generative AI-based tool that translates abstract intentions into creative and structured ideas. This tool facilitates the exploration of suggested related content (knowledge, works, and patterns), enabling users to select, combine, and adjust elements for creative paper-cutting design. A user study (N=16) and an expert evaluation (N=3) demonstrated that HarmonyCut effectively provided relevant knowledge, aiding the ideation of diverse paper-cutting designs and maintaining design quality within the design space to ensure alignment between form and cultural connotation.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- InkIdeator: Supporting Chinese-Style Visual Design Ideation via AI-Infused Exploration of Chinese PaintingsShiwei Wu, Ziyao Gao, Zhendong He, Zongtan He 等CHI 2026 · 被引用 1 次
- Gen-Diaolou: An Integrated AI-Assisted Interactive System for Diachronic Understanding and Preservation of the Kaiping DiaolouLei Han, Yi Gao, Xuanchen Lu, Bingyuan Wang 等CHI 2026 · 被引用 1 次
它引用的顶会 Paper24
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 被引用 64,255 次
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn 等ICLR 2021 · 被引用 21,477 次
- Segment AnythingAlexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao 等ICCV 2023 · 被引用 13,211 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
相关 Paper
- PoemPalette: Facilitating Poetry Creative Exploration and Foundational Understanding through the Ideorealm Alignment of Paintings and PoemsYing Zhang, Kaixin Jia, Hong Jian Zhang, Kewen Zhu 等CHI 2026 · 被引用 1 次
- AIFiligree: A Generative AI Framework for Designing Exquisite Filigree ArtworksYe Tao, Xiaohui Fu, Jiaying Wu, Ze Bian 等CHI 2025 · 被引用 11 次
- Magical Brush: A Symbol-Based Modern Chinese Painting System for NovicesHaoran Xu, Shuyao Chen, Ying ZhangCHI 2023 · 被引用 23 次
- Is It AI or Is It Me? Understanding Users' Prompt Journey with Text-to-Image Generative AI ToolsAtefeh Mahdavi Goloujeh, Anne Sullivan, Brian MagerkoCHI 2024 · 被引用 88 次
- Exploring the Impact of AI-powered Creativity Support Tools on Professional Creative WorkflowsCaterina Moruzzi, Charlotte Bird, Laura Mariah HermanCSCW 2026
