title: GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided
    Generative Gaussian Splatting
summary: 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 the initial layout and introduce a layout-guided 3D
  Gaussian representation for 3D content generation with adaptive geometric
  constraints. We then propose an object-scene compositional optimization
  mechanism with conditioned diffusion to collaboratively generate realistic 3D
  scenes with consistent geometry, texture, scale, and accurate interactions
  among multiple objects while simultaneously adjusting the coarse layout priors
  extracted from the LLMs to align with the generated scene. Experiments show
  that GALA3D is a user-friendly, end-to-end framework for state-of-the-art
  scene-level 3D content generation and controllable editing while ensuring the
  high fidelity of object-level entities within the scene. Source codes and
  models will be available at https://gala3d.github.io/.
paper_authors._id: 65cadb0805cc358d07f5dca4
paper_authors.name: Xiaoyu Zhou
paper_authors._id: 65cadb0805cc358d07f5dca5
paper_authors.name: Xingjian Ran
paper_authors._id: 65cadb0805cc358d07f5dca6
paper_authors.name: Yajiao Xiong
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-13T13:50:48.407Z
paper_authors._id: 658976866cf9325ae6e3a10f
paper_authors.avatarUrl: /avatars/85ef8bdc24191ee3ce3eb277d0223aad.svg
paper_authors.fullname: yajiao xiong
paper_authors.type: user
paper_authors.user: yajiao
paper_authors._id: 65cadb0805cc358d07f5dca7
paper_authors.name: Jinlin He
paper_authors._id: 65cadb0805cc358d07f5dca8
paper_authors.name: Zhiwei Lin
paper_authors._id: 65cadb0805cc358d07f5dca9
paper_authors.name: Yongtao Wang
paper_authors._id: 65cadb0805cc358d07f5dcaa
paper_authors.name: Deqing Sun
paper_authors._id: 65cadb0805cc358d07f5dcab
paper_authors.name: Ming-Hsuan Yang
paper_title: GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided
    Generative Gaussian Splatting
paper_summary: 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 the initial layout and introduce a layout-guided 3D
  Gaussian representation for 3D content generation with adaptive geometric
  constraints. We then propose an object-scene compositional optimization
  mechanism with conditioned diffusion to collaboratively generate realistic 3D
  scenes with consistent geometry, texture, scale, and accurate interactions
  among multiple objects while simultaneously adjusting the coarse layout priors
  extracted from the LLMs to align with the generated scene. Experiments show
  that GALA3D is a user-friendly, end-to-end framework for state-of-the-art
  scene-level 3D content generation and controllable editing while ensuring the
  high fidelity of object-level entities within the scene. Source codes and
  models will be available at https://gala3d.github.io/.
paper_ai_keywords: generative 3D GAussians LAyout-guided control large language models (LLMs) layout-guided 3D Gaussian representation adaptive geometric constraints object-scene compositional optimization conditioned diffusion consistency geometry consistent geometry accurate interactions coarse layout priors state-of-the-art scene-level 3D content generation controllable editing high fidelity of object-level entities