Symmetry Strikes Back: From Single-Image Symmetry Detection to 3D Generation Article Swipe
Xiang Li
,
Zixuan Huang
,
Anh Thai
,
James M. Rehg
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.17763
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.17763
Symmetry is a ubiquitous and fundamental property in the visual world, serving as a critical cue for perception and structure interpretation. This paper investigates the detection of 3D reflection symmetry from a single RGB image, and reveals its significant benefit on single-image 3D generation. We introduce Reflect3D, a scalable, zero-shot symmetry detector capable of robust generalization to diverse and real-world scenarios. Inspired by the success of foundation models, our method scales up symmetry detection with a transformer-based architecture. We also leverage generative priors from multi-view diffusion models to address the inherent ambiguity in single-view symmetry detection. Extensive evaluations on various data sources demonstrate that Reflect3D establishes a new state-of-the-art in single-image symmetry detection. Furthermore, we show the practical benefit of incorporating detected symmetry into single-image 3D generation pipelines through a symmetry-aware optimization process. The integration of symmetry significantly enhances the structural accuracy, cohesiveness, and visual fidelity of the reconstructed 3D geometry and textures, advancing the capabilities of 3D content creation.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2411.17763
- https://arxiv.org/pdf/2411.17763
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404990075
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404990075Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2411.17763Digital Object Identifier
- Title
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Symmetry Strikes Back: From Single-Image Symmetry Detection to 3D GenerationWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-26Full publication date if available
- Authors
-
Xiang Li, Zixuan Huang, Anh Thai, James M. RehgList of authors in order
- Landing page
-
https://arxiv.org/abs/2411.17763Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2411.17763Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2411.17763Direct OA link when available
- Concepts
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Symmetry (geometry), Image (mathematics), Theoretical physics, Geometry, Artificial intelligence, Physics, Computer vision, Mathematics, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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