ICLR 2025poster2 citations

Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint

Junwei Zhou, Xueting Li, Lu Qi, Ming-Hsuan Yang

Abstract

We present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets with plausible object interactions or require tedious optimization processes. To address these challenges, our approach leverages 2D layouts as a blueprint to facilitate precise and plausible control over 3D generation. Starting with a 2D layout provided by a user or generated from a text description, we first create a coarse 3D scene using a carefully designed initialization process based on efficient reconstruction models. To enforce coherent global 3D layouts and enhance the quality of instance appearances, we propose a collision-aware layout optimization process followed by instance-wise refinement. Experimental results demonstrate that Layout-Your-3D yields more reasonable and visually appealing compositional 3D assets while significantly reducing the time required for each prompt. Additionally, Layout-Your-3D can be easily applicable to downstream tasks, such as 3D editing and object insertion.

3D generationgaussian splattingText-to-3Dcompositional asset generation
BibTeX
@inproceedings{
zhou2025layoutyourd,
title={Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint},
author={Junwei Zhou and Xueting Li and Lu Qi and Ming-Hsuan Yang},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=myolhJPuRI}
}
Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint · ICLR 2025