SceneFactor: Factored Latent 3D Diffusion for Controllable 3D Scene Generation

• URL: http://arxiv.org/abs/2412.01801v2
• Date: Tue, 03 Dec 2024 10:32:05 GMT
• Title: SceneFactor: Factored Latent 3D Diffusion for Controllable 3D Scene Generation
• Authors: Alexey Bokhovkin, Quan Meng, Shubham Tulsiani, Angela Dai,
• Abstract summary: SceneFactor is a diffusion-based approach for large-scale 3D scene generation. It enables controllable generation and effortless editing. Our approach enables high-fidelity 3D scene synthesis with effective controllable editing.
• Score: 44.354071773885735
• License:
• Abstract: We present SceneFactor, a diffusion-based approach for large-scale 3D scene generation that enables controllable generation and effortless editing. SceneFactor enables text-guided 3D scene synthesis through our factored diffusion formulation, leveraging latent semantic and geometric manifolds for generation of arbitrary-sized 3D scenes. While text input enables easy, controllable generation, text guidance remains imprecise for intuitive, localized editing and manipulation of the generated 3D scenes. Our factored semantic diffusion generates a proxy semantic space composed of semantic 3D boxes that enables controllable editing of generated scenes by adding, removing, changing the size of the semantic 3D proxy boxes that guides high-fidelity, consistent 3D geometric editing. Extensive experiments demonstrate that our approach enables high-fidelity 3D scene synthesis with effective controllable editing through our factored diffusion approach.

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