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January 1, 2025IEEE Transactions on Pattern Analysis and Machine Intelligence

LN3DIFF++: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation

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Key Points

LN3DIFF++ achieves improved 3D generation speed and quality.
Generative models and diffusion model are fundamental to its architecture.
3D-aware architecture decodes latent representations efficiently.
Rapid inference with no need for per-instance optimization.

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Implication

Novel LN3DIFF++ framework generates high-quality 3D models rapidly using a diffusion model, implying faster neural rendering.

Cite This Study

Lan et al. (2025) studied this question.

synapsesocial.com/papers/6925573bc0ce034ddc35b25c https://doi.org/10.1109/tpami.2025.3633073

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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1LN3Diff: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation2024
2Part-aware Shape Generation with Latent 3D Diffusion of Neural Voxel Fields2024
3Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer2024 · 9 citations
4NeuroDiff3D: a 3D generation method optimizing viewpoint consistency through diffusion modeling2025
53D MedDiffusion: A 3D Medical Latent Diffusion Model for Controllable and High-Quality Medical Image GenerationOriginal Research · 2025 · 34 citations