A11yShape: AI-Assisted 3-D Modeling for Blind and Low-Vision Programmers
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Abstract (arXiv)
Building 3-D models is challenging for blind and low-vision (BLV) users due to the inherent complexity of 3-D models and the lack of support for non-visual interaction in existing tools. To address this issue, we introduce A11yShape, a novel system designed to help BLV users who possess basic programming skills understand, modify, and iterate on 3-D models. A11yShape leverages LLMs and integrates with OpenSCAD, a popular open-source editor that generates 3-D models from code. Key functionalities of A11yShape include accessible descriptions of 3-D models, version control to track changes in models and code, and a hierarchical representation of model components. Most importantly, A11yShape employs a cross-representation highlighting mechanism to synchronize semantic selections across all model representations -- code, semantic hierarchy, AI description, and 3-D rendering. We conducted a multi-session user study with four BLV programmers, where, after an initial tutorial session, participants independently completed 12 distinct models across two testing sessions, achieving results that aligned with their own satisfaction. The result demonstrates that participants were able to comprehend provided 3-D models, as well as independently create and modify 3-D models -- tasks that were previously impossible without assistance from sighted individuals.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Aug 2025.
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Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2026Alignment-Process-Outcome: Rethinking How AIs and Humans Collaboratecited by 1
- 2026Three Modalities, Two Design Probes, One Prototype, and No Vision: Experience-Based Co-Design of a Multi-modal 3D Data Visualization Toolcited by 1
- 2025MedBuild AI: An Agent-Based Hybrid Intelligence Framework for Reshaping Agency in Healthcare Infrastructure Planning through Generative Design for Medical Architecturecited by 0
- 2026InstructMesh: Selective Refinement of Generative 3D Models for Fabricationcited by 0
- 2026InstructMesh: Selective Refinement of Generative 3D Models for Fabrication28 Aug 2026
- 2026Three Modalities, Two Design Probes, One Prototype, and No Vision: Experience-Based Co-Design of a Multi-modal 3D Data Visualization Tool10 Apr 2026
- 2026Alignment-Process-Outcome: Rethinking How AIs and Humans Collaborate9 Mar 2026
- 2025MedBuild AI: An Agent-Based Hybrid Intelligence Framework for Reshaping Agency in Healthcare Infrastructure Planning through Generative Design for Medical Architecture17 Oct 2025