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

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arxiv 2412.01801 v2 pith:U4JQKN7J submitted 2024-12-02 cs.CV

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

classification cs.CV
keywords controllableeditingenablesgenerationsemanticdiffusionfactoredscene
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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Cited by 1 Pith paper

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  1. EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learning

    cs.CV 2026-07 conditional novelty 6.0

    An end-to-end 3D editing framework achieves high-fidelity local edits from coarse bounding boxes and 2D image prompts using region-aware loss reweighting and a large-scale parts-derived training dataset.