Quartet of Diffusions: Structure-Aware Point Cloud Generation through Part and Symmetry Guidance
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Abstract (arXiv)
We introduce the Quartet of Diffusions, a structure-aware point cloud generation framework that explicitly models part composition and symmetry. Unlike prior methods that treat shape generation as a holistic process or only support part composition, our approach leverages four coordinated diffusion models to learn distributions of global shape latents, symmetries, semantic parts, and their spatial assembly. This structured pipeline ensures guaranteed symmetry, coherent part placement, and diverse, high-quality outputs. By disentangling the generative process into interpretable components, our method supports fine-grained control over shape attributes, enabling targeted manipulation of individual parts while preserving global consistency. A central global latent further reinforces structural coherence across assembled parts. Our experiments show that the Quartet achieves state-of-the-art performance. To our best knowledge, this is the first 3D point cloud generation framework that fully integrates and enforces both symmetry and part priors throughout the generative process.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 72 of its 134 references that are in the map. First posted on arXiv 28 Jan 2026.
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72 of 134 references.
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- 2025PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion
- 2024Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion Models
- 2025Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion
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