2 citations · 3 across the 4 of their papers we have counts for
5 papers
SceneMosaic: Efficient and Diverse Simulation-Ready Scene Generation via Hybrid Agentic Layout Evolution
Xingjian Ran, Xiaoye Mo, Sihao Liu +3
Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet their scalable generation remains challenging. Recent agentic text-to-3D…
Pair2Scene: Learning Local Object Relations for Procedural Scene Generation
Xingjian Ran, Shujie Zhang, Weipeng Zhong +2
Generating high-fidelity 3D indoor scenes remains a significant challenge due to data scarcity and the complexity of modeling intricate spatial relations. Current methods often str…
Direct Numerical Layout Generation for 3D Indoor Scene Synthesis via Spatial Reasoning
Xingjian Ran, Yixuan Li, Linning Xu +2
Realistic 3D indoor scene synthesis is vital for embodied AI and digital content creation. It can be naturally divided into two subtasks: object generation and layout generation. W…
Proc-GS: Procedural Building Generation for City Assembly with 3D Gaussians
Yixuan Li, Xingjian Ran, Linning Xu +6
Buildings are primary components of cities, often featuring repeated elements such as windows and doors. Traditional 3D building asset creation is labor-intensive and requires spec…
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong +5
We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate…