Learning part-based templates from large collections of 3D shapes

DOI10.1145/2461912.2461933zbMath1305.68249OpenAlexW2031760064MaRDI QIDQ5174709

Wilmot Li, Thomas Funkhouser, Stephen Diverdi, Niloy J. Mitra, Siddhartha Chaudhuri, Vladimir G. Kim

Publication date: 18 February 2015

Published in: ACM Transactions on Graphics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1145/2461912.2461933

zbMATH Keywords

segmentationcorrespondenceshape analysismodel collectionspart-based template

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Approximation algorithms (68W25) Computer-aided design (modeling of curves and surfaces) (65D17)

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Structure-aware shape correspondence network for 3D shape synthesis ⋮ Diffusion pruning for rapidly and robustly selecting global correspondences using local isometry ⋮ EdgeNet: deep metric learning for 3D shapes

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