Multi-resolution 3D CNN for learning multi-scale spatial features in CAD models

DOI10.1016/j.cagd.2021.102038zbMath1480.65055OpenAlexW3204631764MaRDI QIDQ2065636

Xian Yeow Lee, Soumik Sarkar, Aditya Balu, Adarsh Krishnamurthy, Sambit Ghadai

Publication date: 12 January 2022

Published in: Computer Aided Geometric Design (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cagd.2021.102038

zbMATH Keywords

interpretabilityobject recognitiondeep learningmulti-level voxel representationmulti-resolution CNN

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18)

Related Items (1)

D3AdvM: A direct 3D adversarial sample attack inside mesh data

Uses Software

• DiffSharp
• ImageNet
• PointNet
• Grad-CAM
• OctNet
• VoxNet
• AlexNet
• PyG
• MinkowskiEngine

Cites Work

• Unnamed Item
• Graph-based heuristics for recognition of machined features from a 3D solid model
• Learning localized features in 3D CAD models for manufacturability analysis of drilled holes

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