PartSDF: Part-Based Implicit Neural Representation for Composite 3D Shape Parametrization and Optimization Article Swipe
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· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2502.12985
Accurate 3D shape representation is essential in engineering applications such as design, optimization, and simulation. In practice, engineering workflows require structured, part-based representations, as objects are inherently designed as assemblies of distinct components. However, most existing methods either model shapes holistically or decompose them without predefined part structures, limiting their applicability in real-world design tasks. We propose PartSDF, a supervised implicit representation framework that explicitly models composite shapes with independent, controllable parts while maintaining shape consistency. Thanks to its simple but innovative architecture, PartSDF outperforms both supervised and unsupervised baselines in reconstruction and generation tasks. We further demonstrate its effectiveness as a structured shape prior for engineering applications, enabling precise control over individual components while preserving overall coherence. Code available at https://github.com/cvlab-epfl/PartSDF.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2502.12985
- https://arxiv.org/pdf/2502.12985
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407760015
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407760015Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2502.12985Digital Object Identifier
- Title
-
PartSDF: Part-Based Implicit Neural Representation for Composite 3D Shape Parametrization and OptimizationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-02-18Full publication date if available
- Authors
-
Nicolas Talabot, Olivier Clerc, Arda Cinar Demirtas, Doruk Oner, Pascal FuaList of authors in order
- Landing page
-
https://arxiv.org/abs/2502.12985Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2502.12985Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2502.12985Direct OA link when available
- Concepts
-
Parametrization (atmospheric modeling), Composite number, Representation (politics), Mathematics, Computer science, Algorithm, Physics, Political science, Law, Politics, Radiative transfer, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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