4 papers
BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding
Muhammad Usama, Didier Stricker, Mohammad Sadil Khan +1
Learning representations of CAD models is a largely open problem. While 3D representation learning has flourished around point clouds and meshes, the native format of CAD - boundar…
DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces
Mohammad Sadil Khan, Muhammad Usama, Rolandos Alexandros Potamias +4
Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit d…
NURBGen: High-Fidelity Text-to-CAD Generation through LLM-Driven NURBS Modeling
Muhammad Usama, Mohammad Sadil Khan, Didier Stricker +1
Generating editable 3D CAD models from natural language remains challenging, as existing text-to-CAD systems either produce meshes or rely on scarce design-history data. We present…
MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation
Sankalp Sinha, Mohammad Sadil Khan, Muhammad Usama +4
Generating high-fidelity 3D content from text prompts remains a significant challenge in computer vision due to the limited size, diversity, and annotation depth of the existing da…