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Computer Science > Human-Computer Interaction

arXiv:2510.11941 (cs)
[Submitted on 13 Oct 2025]

Title:Refashion: Reconfigurable Garments via Modular Design

Authors:Rebecca Lin, Michal Lukac, Mackenzie Leake
View a PDF of the paper titled Refashion: Reconfigurable Garments via
Modular Design, by Rebecca Lin and 2 other authors
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    Abstract:While bodies change over time and trends vary, most
    store-bought clothing comes in fixed sizes and styles and fails
    to adapt to these changes. Alterations can enable small changes
    to otherwise static garments, but these changes often require
    sewing and are non-reversible. We propose a modular approach to
    garment design that considers resizing, restyling, and reuse
    earlier in the design process. Our contributions include a
    compact set of modules and connectors that form the building
    blocks of modular garments, a method to decompose a garment into
    modules via integer linear programming, and a digital design tool
    that supports modular garment design and simulation. Our user
    evaluation suggests that our approach to modular design can
    support the creation of a wide range of garments and can help
    users transform them across sizes and styles while reusing the
    same building blocks.

Comments:          18 pages, 28 figures
Subjects:          Human-Computer Interaction (cs.HC)
ACM classes:       H.5.2; J.6
Cite as:           arXiv:2510.11941 [cs.HC]
                   (or arXiv:2510.11941v1 [cs.HC] for this version)
                   https://doi.org/10.48550/arXiv.2510.11941
                   Focus to learn more
                   arXiv-issued DOI via DataCite
                   Proceedings of the 38th Annual ACM Symposium on
Journal reference: User Interface Software and Technology (UIST '25),
                   Article 102, pp. 1-18, 2025
                   https://doi.org/10.1145/3746059.3747632
Related DOI:       Focus to learn more
                   DOI(s) linking to related resources

Submission history

From: Rebecca Lin [view email]
[v1] Mon, 13 Oct 2025 21:04:58 UTC (35,570 KB)
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