TerraCraft: City-scale generative procedural modeling with natural languages
Automated generation of large-scale 3D scenes presents a significant challenge due to the resource-intensive training and datasets required. This is in sharp contrast to the 2D counterparts that have become readily available due to their superior speed and quality. However, prior work in 3D procedural modeling has demonstrated promise in generating high-quality assets using the combination of algorithms and user-defined rules. To leverage the best of both 2D generative models and procedural modeling tools, we present TerraCraft, a novel framework for generating geometrically high-quality 3D city-scale scenes. By utilizing Large Language Models (LLMs), TerraCraft can generate city-scale 3D scenes from natural text descriptions. With its intuitive operation and powerful capabilities, TerraCraft enables users to easily create geometrically high-quality scenes readily for various applications, such as virtual reality and game design. We validate TerraCraft’s effectiveness through extensive experiments and user studies, showing its superior performance compared to existing baselines.
Authors
- Zulian Xi
- Hongyu Yan
- Tai‐Jiang Mu (ORCID: https://orcid.org/0000-0002-9197-346X)
- Jiahui Huang (ORCID: https://orcid.org/0000-0001-6320-2636)
- Zifeng Lü (ORCID: https://orcid.org/0000-0001-7331-5861)
- Qun‐Ce Xu
- Zhigang Wang (ORCID: https://orcid.org/0000-0002-4299-1717)
- Zhihao Yao (ORCID: https://orcid.org/0009-0003-9638-7413)
Institutions
- Nvidia (United States) (US)
- Tsinghua University (CN)
Publication Details
- Journal
- Graphical Models
- Published
- 2025-08-05
- DOI
- https://doi.org/10.1016/j.gmod.2025.101285
- Citations
- 1
- Primary Topic
- 3D Modeling in Geospatial Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.01