Problem
Research questions and friction points this paper is trying to address.
Text-to-CAD
spatial constraints
construction structure
natural-language descriptions
ExpConCAD: Experience-Guided Text-to-CAD Generation from Shape Descriptions with Implicit Spatial Constraints
🤖 AI Summary
本文针对文本到CAD生成中空间约束缺失的问题，提出ExpConCAD框架，通过理解构建结构和借鉴设计经验来补全隐式空间约束。
📝 Abstract
Text-to-CAD aims to generate executable CAD programs from natural-language descriptions. However, real-world descriptions are often underspecified and omit critical spatial constraints required for valid CAD construction, a challenge that has been largely overlooked by existing methods. In this paper, we argue that missing spatial constraints should be inferred with respect to the underlying construction structure and informed by reusable design experience. Based on this insight, we propose ExpConCAD, an experience-enhanced framework for implicit spatial constraint completion. ExpConCAD first recovers the intended construction structure and constraint scopes, then retrieves relevant constraint-completion experience for similar scopes to complete the missing spatial constraints, and finally generates executable CadQuery programs. Extensive experiments demonstrate the effectiveness of ExpConCAD and provide insights into the role of construction structure understanding and experience memory in spatial constraint completion. Our code is available at: https://github.com/Hotjiashell/ExpConCAD.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Experience-Guided
Spatial Constraints
Construction Structure
Text-to-CAD
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