no code implementations • 21 Apr 2024 • Ran Chen, Zeke Lian, Yueheng He, Xiao Ling, Fuyu Yang, Xueqi Yao, Xingjian Yi, Jing Zhao
Experimental results show that: (1) the system, with the aid of AI-assisted technology, can rapidly generate space green space schemes that meet the designer's perspective based on site conditions; (2) this study has vectorized and three-dimensionalized various types of landscape design elements based on semantic information; (3) the analysis and visualization module constructed in this study can perform landscape analysis on the generated three-dimensional models and produce node effect diagrams, allowing users to modify the design in real time based on the effects, thus enhancing the system's interactivity.
no code implementations • 17 Dec 2023 • Ran Chen, Xingjian Yi, Jing Zhao, Yueheng He, Bainian Chen, Xueqi Yao, Fangjun Liu, Haoran Li, Zeke Lian
There are two research gaps in the current research: 1) Most studies only focus on the relationship between design elements and pay little attention to the external information of the site; 2) GAN and other traditional generative algorithms generate results with low resolution and insufficient details.
