mlsanityData to 7 Oct 2026

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

arXiv 2403.12019 ↗First posted 18 Mar 2024cs.CVcited by 91

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Cited by 25 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved success, a unified 3D diffusion pipeline remains unsettled. This paper introduces a novel framework called LN3Diff++ to address this gap and enable fast, high-quality, and generic conditional 3D generation. Our approach harnesses a 3D-aware architecture and variational autoencoder (VAE) to encode the input image into a structured, compact, and 3D latent space. The latent is decoded by a transformer-based decoder into a high-capacity 3D neural field. Through training a diffusion model on this 3D-aware latent space, our method achieves state-of-the-art performance on ShapeNet for 3D generation and demonstrates superior performance in monocular 3D reconstruction and conditional 3D generation across various datasets. Moreover, it surpasses existing 3D diffusion methods in terms of inference speed, requiring no per-instance optimization. Our proposed LN3Diff presents a significant advancement in 3D generative modeling and holds promise for various applications in 3D vision and graphics tasks.

Key facts. Cited by 91 papers in the map (data through 7 Oct 2026). Builds on 122 of its 157 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

122 of 157 references.

References · 122

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38 more
  1. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  2. 2022Scalable Diffusion Models with Transformerscited by 5,931
  3. 2022Classifier-Free Diffusion Guidancecited by 5,717
  4. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  5. 2022Flow Matching for Generative Modelingcited by 5,426
  6. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
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  13. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  14. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
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  16. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  17. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
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  19. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
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50 most cited of 122 All 122 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 23; 2025: 40; 2026: 28.

91 papers.

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  1. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
  2. 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 342
  3. 2024Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformercited by 210
  4. 2025Native and Compact Structured Latents for 3D Generationcited by 157
  5. 20243DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusioncited by 100
  6. 2024Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoderscited by 93
  7. 2024EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generationcited by 84
  8. 2025SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modelingcited by 76
  9. 2024SF3D: Stable Fast 3D Mesh Reconstruction with UV-unwrapping and Illumination Disentanglementcited by 65
  10. 2025OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesioncited by 60
  11. 2025HoloPart: Generative 3D Part Amodal Segmentationcited by 57
  12. 2024LT3SD: Latent Trees for 3D Scene Diffusioncited by 53
38 more
  1. 2025DiffSplat: Repurposing Image Diffusion Models for Scalable Gaussian Splat Generationcited by 49
  2. 2025Efficient Part-level 3D Object Generation via Dual Volume Packingcited by 47
  3. 2025Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attentioncited by 43
  4. 2025SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single Imagescited by 41
  5. 2024SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAEcited by 38
  6. 2024Prometheus: 3D-Aware Latent Diffusion Models for Feed-Forward Text-to-3D Scene Generationcited by 33
  7. 2025Gaussian Variation Field Diffusion for High-fidelity Video-to-4D Synthesiscited by 33
  8. 2025AToken: A Unified Tokenizer for Visioncited by 30
  9. 2025OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generationcited by 27
  10. 2025LL3M: Large Language 3D Modelerscited by 18
  11. 2025FastMesh: Efficient Artistic Mesh Generation via Component Decouplingcited by 17
  12. 2024LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusioncited by 16
  13. 2024TAR3D: Creating High-Quality 3D Assets via Next-Part Predictioncited by 16
  14. 2025WorldGrow: Generating Infinite 3D Worldcited by 14
  15. 2024Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curationcited by 12
  16. 2024GaussianAnything: Interactive Point Cloud Flow Matching For 3D Object Generationcited by 12
  17. 20243DEnhancer: Consistent Multi-View Diffusion for 3D Enhancementcited by 12
  18. 2024Sampling 3D Gaussian Scenes in Seconds with Latent Diffusion Modelscited by 10
  19. 2025ArtiLatent: Realistic Articulated 3D Object Generation via Structured Latentscited by 10
  20. 2024Reference-Based 3D-Aware Image Editing with Triplanescited by 9
  21. 2024DNF: Unconditional 4D Generation with Dictionary-based Neural Fieldscited by 8
  22. 2025Zero-1-to-G: Taming Pretrained 2D Diffusion Model for Direct 3D Generationcited by 8
  23. 2025Towards Scalable Spatial Intelligence via 2D-to-3D Data Liftingcited by 8
  24. 2024Fancy123: One Image to High-Quality 3D Mesh Generation via Plug-and-Play Deformationcited by 7
  25. 2024Symmetry Strikes Back: From Single-Image Symmetry Detection to 3D Generationcited by 7
  26. 2025MARS: Mesh AutoRegressive Model for 3D Shape Detailizationcited by 7
  27. 2025Hyper3D: Efficient 3D Representation via Hybrid Triplane and Octree Feature for Enhanced 3D Shape Variational Auto-Encoderscited by 7
  28. 2025Repurposing 2D Diffusion Models with Gaussian Atlas for 3D Generationcited by 7
  29. 2025Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Datacited by 7
  30. 2025Textured 3D Regenerative Morphing with 3D Diffusion Priorcited by 6
  31. 2025Representing 3D Shapes With 64 Latent Vectors for 3D Diffusion Modelscited by 6
  32. 2025TeRA: Rethinking Text-guided Realistic 3D Avatar Generationcited by 5
  33. 2025MajutsuCity: Language-driven Aesthetic-adaptive City Generation with Controllable 3D Assets and Layoutscited by 5
  34. 2026Learn2Fold: Structured Origami Generation with World Model Planningcited by 5
  35. 2024MicroDreamer: Efficient 3D Generation in ~20 Seconds by Score-based Iterative Reconstructioncited by 4
  36. 2025MASH: Masked Anchored SpHerical Distances for 3D Shape Representation and Generationcited by 4
  37. 2025VaseVQA-3D: Benchmarking 3D VLMs on Ancient Greek Potterycited by 4
  38. 2025GaMO: Geometry-aware Multi-view Diffusion Outpainting for Sparse-View 3D Reconstructioncited by 4

50 most cited of 91 All 91 (JSON)

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  1. 2023Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images
  2. 2024L3DG: Latent 3D Gaussian Diffusion
  3. 2023WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space
  4. 20223D-LDM: Neural Implicit 3D Shape Generation with Latent Diffusion Models
  5. 20233D-CLFusion: Fast Text-to-3D Rendering with Contrastive Latent Diffusion
  6. 2024Part-aware Shape Generation with Latent 3D Diffusion of Neural Voxel Fields
  7. 2024Wavelet Latent Diffusion (Wala): Billion-Parameter 3D Generative Model with Compact Wavelet Encodings
  8. 2024BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapolation