Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > cs > arXiv:2510.16223

Help | Advanced Search

Computer Science > Human-Computer Interaction

arXiv:2510.16223 (cs)
[Submitted on 17 Oct 2025 ]

Title: Case Study of GAI for Generating Novel Images for Real-World Embroidery

Title: GAI在生成现实世界刺绣新图像中的案例研究

Authors:Kate Glazko, Anika Arugunta, Janelle Chan, Nancy Jimenez-Garcia, Tashfia Sharmin, Jennifer Mankoff
Abstract: In this paper, we present a case study exploring the potential use of Generative Artificial Intelligence (GAI) to address the real-world need of making the design of embroiderable art patterns more accessible. Through an auto-ethnographic case study by a disabled-led team, we examine the application of GAI as an assistive technology in generating embroidery patterns, addressing the complexity involved in designing culturally-relevant patterns as well as those that meet specific needs regarding detail and color. We detail the iterative process of prompt engineering custom GPTs tailored for producing specific visual outputs, emphasizing the nuances of achieving desirable results that align with real-world embroidery requirements. Our findings underscore the mixed outcomes of employing GAI for producing embroiderable images, from facilitating creativity and inclusion to navigating the unpredictability of AI-generated designs. Future work aims to refine GAI tools we explored for generating embroiderable images to make them more performant and accessible, with the goal of fostering more inclusion in the domains of creativity and making.
Abstract: 在本文中,我们进行了一项案例研究,探讨生成式人工智能(GAI)在解决使可刺绣艺术图案设计更易于使用的真实需求方面的潜力。通过一个由残疾人领导的团队进行的自民族志案例研究,我们考察了GAI作为辅助技术在生成刺绣图案中的应用,解决了设计具有文化相关性的图案以及满足细节和颜色特定需求的复杂性。我们详细描述了为产生特定视觉输出而定制GPT的迭代过程,强调了实现符合现实世界刺绣要求的期望结果的细微差别。我们的研究结果强调了使用GAI生成可刺绣图像的混合结果,从促进创造力和包容性到应对AI生成设计的不可预测性。未来的工作旨在改进我们探索的生成可刺绣图像的GAI工具,使其更具性能和可访问性,以促进创造力和制作领域的更多包容性。
Comments: Published as a workshop paper at GenAICHI: CHI 2024 Workshop on Generative AI and HCI (https://generativeaiandhci.github.io/papers/2024/genaichi2024_54.pdf)
Subjects: Human-Computer Interaction (cs.HC) ; Computers and Society (cs.CY)
Cite as: arXiv:2510.16223 [cs.HC]
  (or arXiv:2510.16223v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2510.16223
arXiv-issued DOI via DataCite
Journal reference: GenAICHI: CHI 2024 Workshop on Generative AI and HCI

Submission history

From: Kate Glazko [view email]
[v1] Fri, 17 Oct 2025 21:16:23 UTC (5,185 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • HTML (experimental)
  • TeX Source
license icon view license
Current browse context:
cs.HC
< prev   |   next >
new | recent | 2025-10
Change to browse by:
cs
cs.CY

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号