GaussianCity: Generative Gaussian Splatting for Unbounded 3D City Generation Haozhe Xie, Zhaoxi Chen, Fangzhou Hong, Ziwei Liu
S-Lab, Nanyang Technological University
TL;DR: GaussianCity is a framework for efficient unbounded 3D city generation using 3D Gaussian Splatting. Abstract 3D city generation with NeRF-based methods shows promising generation results but is computationally inefficient. Recently 3D Gaussian Splatting (3D-GS) has emerged as a highly efficient alternative for object-level 3D generation. However, adapting 3D-GS from finite-scale 3D objects and humans to infinite-scale 3D cities is non-trivial.
CityDreamer: Compositional Generative Model of Unbounded 3D Cities Haozhe Xie, Zhaoxi Chen, Fangzhou Hong, Ziwei Liu
S-Lab, Nanyang Technological University
TL;DR: CityDreamer learns to generate unbounded 3D cities from Google Earth imagery and OpenStreetMap. Abstract In recent years, extensive research has focused on 3D natural scene generation, but the domain of 3D city generation has not received as much exploration. This is due to the greater challenges posed by 3D city generation, mainly because humans are more sensitive to structural distortions in urban environments.