4 papers · 1 filter
ConCAD: Constraint-Aware Image-to-CAD Generation with Dual-Granularity Rewards
Chenxi Zhai, Xi Cheng, Hang Cheng +5
Image-to-CAD generation seeks executable parametric programs that recover both the geometry and design intent of a reference object. Existing systems are commonly evaluated by vali…
DIP-CAD: A Design-Intent-Preserving Agent Harness for Parametric CAD Modeling
Xi Cheng, Chenxi Zhai, Hang Cheng +3
Parametric CAD modeling requires not only matching the target shape, but also preserving design intent under parameter edits. However, most existing methods focus on improving stat…
Constraint-Aware Feature Learning for Parametric Point Cloud
Xi Cheng, Ruiqi Lei, Di Huang +5
Parametric point clouds are sampled from CAD shapes and are becoming increasingly common in industrial manufacturing. Most CAD-specific deep learning methods focus on geometric fea…
Training-Free Point Cloud Recognition Based on Geometric and Semantic Information Fusion
Yan Chen, Di Huang, Zhichao Liao +3
The trend of employing training-free methods for point cloud recognition is becoming increasingly popular due to its significant reduction in computational resources and time costs…