Text-to-hierarchical three-dimensional scene generation: a new approach for layered three-dimensional modeling from natural language
Rapid advancements in generative models have enabled substantial progress in text-to-3D scene synthesis. However, existing approaches often lack hierarchical structure and geometric consistency, limiting their use in complex, editable scene creation. To address this issue, an end-to-end hierarchical framework for text-to-3D scene generation is introduced. The main contribution of this study lies not in advancing a single generative model but in the design of a framework that synergistically integrates state-of-the-art components for video synthesis and mesh reconstruction. By decoupling scene semantics from dynamic camera trajectory control, the proposed system efficiently produces structured object-level editable three-dimensional scenes from natural language. Comprehensive experiments showed that the proposed integrated approach achieved superior scene quality, consistency, and editing flexibility compared with existing methods, offering a powerful solution for applications, such as virtual reality and digital twins.
Authors
- Zuan Gu (ORCID: https://orcid.org/0009-0005-9846-6945)
- Huimin Liu (ORCID: https://orcid.org/0000-0001-6224-5124)
- Tianhan Gao (ORCID: https://orcid.org/0000-0002-9250-3777)
- Lanxu Zhao
Institutions
- Northeastern University (CN)
Publication Details
- Journal
- Visual Computing for Industry Biomedicine and Art
- Published
- 2026-08-26
- DOI
- https://doi.org/10.1186/s42492-026-00226-0
- Primary Topic
- Generative Adversarial Networks and Image Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00