research-article

Meta-representation of shape families

Authors:

Melinos Averkiou,

Oliver van Kaick,

Olga Sorkine-Hornung,

Daniel Cohen-Or,

Niloy J. MitraAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 33, Issue 4

Article No.: 34, Pages 1 - 11

https://doi.org/10.1145/2601097.2601185

Published: 27 July 2014 Publication History

Abstract

We introduce a meta-representation that represents the essence of a family of shapes. The meta-representation learns the configurations of shape parts that are common across the family, and encapsulates this knowledge with a system of geometric distributions that encode relative arrangements of parts. Thus, instead of predefined priors, what characterizes a shape family is directly learned from the set of input shapes. The meta-representation is constructed from a set of co-segmented shapes with known correspondence. It can then be used in several applications where we seek to preserve the identity of the shapes as members of the family. We demonstrate applications of the meta-representation in exploration of shape repositories, where interesting shape configurations can be examined in the set; guided editing, where models can be edited while maintaining their familial traits; and coupled editing, where several shapes can be collectively deformed by directly manipulating the distributions in the meta-representation. We evaluate the efficacy of the proposed representation on a variety of shape collections.

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Cited By

Groscot RCohen L(2024)Unified Shape Analysis and Synthesis via Deformable Voxel GridsComputer Vision, Imaging and Computer Graphics Theory and Applications10.1007/978-3-031-66743-5_2(24-47)Online publication date: 22-Aug-2024
https://doi.org/10.1007/978-3-031-66743-5_2
Kodnongbua MJones BAhmad MKim VSchulz A(2023)ReparamCAD: Zero-shot CAD Re-Parameterization for Interactive ManipulationSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618219(1-12)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.1145/3610548.3618219
Pandey KChevalier FSingh K(2023)Juxtaform: interactive visual summarization for exploratory shape designACM Transactions on Graphics10.1145/359243642:4(1-14)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592436
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Index Terms

Meta-representation of shape families
1. Computing methodologies
  1. Computer graphics
    1. Shape modeling
2. Theory of computation
  1. Randomness, geometry and discrete structures

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 33, Issue 4

July 2014

1366 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2601097

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Copyright © 2014 ACM.

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Association for Computing Machinery

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Publication History

Published: 27 July 2014

Published in TOG Volume 33, Issue 4

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Cited By

Groscot RCohen L(2024)Unified Shape Analysis and Synthesis via Deformable Voxel GridsComputer Vision, Imaging and Computer Graphics Theory and Applications10.1007/978-3-031-66743-5_2(24-47)Online publication date: 22-Aug-2024
https://doi.org/10.1007/978-3-031-66743-5_2
Kodnongbua MJones BAhmad MKim VSchulz A(2023)ReparamCAD: Zero-shot CAD Re-Parameterization for Interactive ManipulationSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618219(1-12)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.1145/3610548.3618219
Pandey KChevalier FSingh K(2023)Juxtaform: interactive visual summarization for exploratory shape designACM Transactions on Graphics10.1145/359243642:4(1-14)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592436
Liu GSun QHuang HMa CGuo YYi LHuang HHu R(2023)Semi-Weakly Supervised Object Kinematic Motion Prediction2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.02081(21726-21735)Online publication date: Jun-2023
https://doi.org/10.1109/CVPR52729.2023.02081
Zhang FFu QLiu YLi X(2023)Component-aware generative autoencoder for structure hybrid and shape completionGraphical Models10.1016/j.gmod.2023.101185129(101185)Online publication date: Oct-2023
https://doi.org/10.1016/j.gmod.2023.101185
Cui JLi SHou FHao AQin H(2023)Analyzing part functionality via multi-modal latent space embedding and interweavingComputers & Graphics10.1016/j.cag.2023.06.031115(1-12)Online publication date: Oct-2023
https://doi.org/10.1016/j.cag.2023.06.031
Roumen TApel IKern TTaraz MSharma RSchlueter OJohnson JMeier DLempert CBaudisch PSchulz ALipton JPeek N(2022)Structure-Preserving Editing of Plates and Volumes for Laser CuttingProceedings of the 7th Annual ACM Symposium on Computational Fabrication10.1145/3559400.3561996(1-12)Online publication date: 26-Oct-2022
https://dl.acm.org/doi/10.1145/3559400.3561996
Groscot RCOHEN L(2022)Deformable voxel grids for shape comparisonsFourteenth International Conference on Digital Image Processing (ICDIP 2022)10.1117/12.2645961(174)Online publication date: 12-Oct-2022
https://doi.org/10.1117/12.2645961
Ma PDu TZhang JWu KSpielberg AKatzschmann RMatusik W(2021)DiffAquaACM Transactions on Graphics10.1145/3450626.345983240:4(1-14)Online publication date: 19-Jul-2021
https://dl.acm.org/doi/10.1145/3450626.3459832
Zheng ZYu TDai QLiu Y(2021)Deep Implicit Templates for 3D Shape Representation2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.00148(1429-1439)Online publication date: Jun-2021
https://doi.org/10.1109/CVPR46437.2021.00148
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