VoxScene: Anchor-Conditioned Voxel Diffusion for Indoor Scene Arrangement

TL;DR

VoxScene introduces an object-centric voxel diffusion method for 3D indoor scene arrangement, ensuring collision-free, high-fidelity layouts with diverse shapes by explicitly modeling volumetric structures.

Contribution

The paper proposes a novel voxel diffusion framework that explicitly models volumetric structures for collision-free, realistic indoor scene synthesis, surpassing existing proxy-based methods.

Findings

Achieves state-of-the-art physical plausibility in scene layouts.

Ensures collision-free arrangements in complex environments.

Provides high-fidelity voxel grids for asset retrieval.

Abstract

We present VoxScene, a novel anchor-conditioned voxel diffusion framework tailored for 3D scene synthesis. Current data-driven layout generation techniques typically rely on bounding proxies or implicit representations, which overlook volumetric structures. This geometric blindness inevitably leads to severe physical collisions and structural entanglement, particularly in densely populated environments. To overcome these limitations, we shift the paradigm to an explicit, object-centric voxel representation. Our pipeline sequentially synthesizes discrete volumetric occupancies conditioned on prior anchors and local context. By exploiting the mutually exclusive nature of discrete voxels, our approach eliminates spatial ambiguities and guarantees collision-free arrangements, even in highly complex environments. Furthermore, the synthesized high-fidelity voxel grids serve as discriminative geometric queries for downstream asset retrieval. Extensive experiments demonstrate the universality of our method, achieving state-of-the-art physical plausibility and unlocking shape diversity compared to existing layout planners.