6 papers · 1 filter
Zero-to-CAD: Agentic Synthesis of Interpretable CAD Programs at Million-Scale Without Real Data
Mohammadmehdi Ataei, Farzaneh Askari, Kamal Rahimi Malekshan +1
Computer-Aided Design (CAD) models are defined by their construction history: a parametric recipe that encodes design intent. However, existing large-scale 3D datasets predominantl…
3D-WAG: Hierarchical Wavelet-Guided Autoregressive Generation for High-Fidelity 3D Shapes
Tejaswini Medi, Arianna Rampini, Pradyumna Reddy +2
Autoregressive (AR) models have achieved remarkable success in natural language and image generation, but their application to 3D shape modeling remains largely unexplored. Unlike…
AutoBrep: Autoregressive B-Rep Generation with Unified Topology and Geometry
Xiang Xu, Pradeep Kumar Jayaraman, Joseph G. Lambourne +3
The boundary representation (B-Rep) is the standard data structure used in Computer-Aided Design (CAD) for defining solid models. Despite recent progress, directly generating B-Rep…
B-Rep Distance Functions (BR-DF): How to Represent a B-Rep Model by Volumetric Distance Functions?
Fuyang Zhang, Pradeep Kumar Jayaraman, Xiang Xu +1
This paper presents a novel geometric representation for CAD Boundary Representation (B-Rep) based on volumetric distance functions, dubbed B-Rep Distance Functions (BR-DF). BR-DF…
BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry
Xiang Xu, Joseph G. Lambourne, Pradeep Kumar Jayaraman +3
This paper presents BrepGen, a diffusion-based generative approach that directly outputs a Boundary representation (B-rep) Computer-Aided Design (CAD) model. BrepGen represents a B…
CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketches
Sifan Wu, Amir Khasahmadi, Mor Katz +4
Parametric Computer-Aided Design (CAD) is central to contemporary mechanical design. However, it encounters challenges in achieving precise parametric sketch modeling and lacks pra…