Conference item
SynCity: training-free generation of 3D cities
- Abstract:
- We propose SynCity, a method for generating explorable 3D worlds from textual descriptions. Our approach leverages pre-trained textual, image, and 3D generators without requiring fine-tuning or inference-time optimization. While most 3D generators are object-centric and unable to create large-scale worlds, we demonstrate how 2D and 3D generators can be combined to produce ever-expanding scenes. The world is generated tile by tile, with each new tile created within its context and seamlessly integrated into the scene. SynCity enables fine-grained control over the appearance and layout of the generated worlds, which are both detailed and diverse.
- Publication status:
- Accepted
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 36.1MB, Terms of use)
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Authors
- Publisher:
- IEEE
- Acceptance date:
- 2025-07-23
- Event title:
- International Conference on Computer Vision (ICCV 2025)
- Event location:
- Honolulu, Hawai'i
- Event website:
- https://iccv.thecvf.com/
- Event start date:
- 2025-10-19
- Event end date:
- 2025-10-23
- Language:
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English
- Pubs id:
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2300501
- Local pid:
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pubs:2300501
- Deposit date:
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2025-10-20
- ARK identifier:
Terms of use
- Notes:
- This paper was presented at the International Conference on Computer Vision (ICCV 2025), 19th-23rd October 2025, Honolulu, Hawai'i. The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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