mlsanityData to 7 Oct 2026

HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation

arXiv 2307.16183 ↗First posted 30 Jul 2023cs.CVcited by 27

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models. Recent progress (Magic3D) in text-to-3D has shown that employing high-resolution (e.g., 512 x 512) renderings can lead to the production of high-quality 3D models using latent diffusion priors. To enable rendering at even higher resolutions, which has the potential to further augment the quality and detail of the models, we propose a novel approach that combines multiple noise estimation processes with a pretrained 2D diffusion prior. Distinct from the Bar-Tal et al.s' study which binds multiple denoised results to generate images from texts, our approach integrates the computation of scoring distillation losses such as SDS loss and VSD loss which are essential techniques for the 3D content generation with 2D diffusion priors. We experimentally evaluated the proposed approach. The results show that the proposed approach can generate high-quality details compared to the baselines.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 25 of its 31 references that are in the map. First posted on arXiv 30 Jul 2023.

Builds on

25 of 31 references.

Closest ancestors · 4

Same direction, newest first

  1. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation25 May
  2. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation24 Mar
  3. 2022Magic3D: High-Resolution Text-to-3D Content Creation18 Nov
  4. 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep

Other references · 21

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  6. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  7. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  8. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  9. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  10. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  11. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
  12. 20163D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstructioncited by 587
9 more
  1. 2023MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generationcited by 529
  2. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  3. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
  4. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
  5. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 401
  6. 2019Pushing the Boundaries of View Extrapolation with Multiplane Imagescited by 191
  7. 2022Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Qualitycited by 181
  8. 2019Neural Volumes: Learning Dynamic Renderable Volumes from Imagescited by 173
  9. 2022DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decodercited by 27

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Cited by year

Citing papers per year: 2023: 10; 2024: 11; 2025: 6.

27 papers.

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  1. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 682
  2. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 638
  3. 2024CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assetscited by 444
  4. 2023GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Modelscited by 255
  5. 2023RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3Dcited by 168
  6. 2024SPAD : Spatially Aware Multiview Diffuserscited by 62
  7. 2024Director3D: Real-world Camera Trajectory and 3D Scene Generation from Textcited by 50
  8. 2024Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Videocited by 44
  9. 2023HiFi-123: Towards High-fidelity One Image to 3D Content Generationcited by 34
  10. 2023Disentangled Clothed Avatar Generation from Text Descriptionscited by 33
  11. 2023Repaint123: Fast and High-quality One Image to 3D Generation with Progressive Controllable 2D Repaintingcited by 25
  12. 2024Diffusion Time-step Curriculum for One Image to 3D Generationcited by 20
15 more
  1. 2023Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clippingcited by 17
  2. 2023DPoser: Diffusion Model as Robust 3D Human Pose Priorcited by 17
  3. 2023Efficient-NeRF2NeRF: Streamlining Text-Driven 3D Editing with Multiview Correspondence-Enhanced Diffusion Modelscited by 16
  4. 2024DreamCar: Leveraging Car-specific Prior for in-the-wild 3D Car Reconstructioncited by 15
  5. 2024Envision3D: One Image to 3D with Anchor Views Interpolationcited by 12
  6. 2024Dual3D: Efficient and Consistent Text-to-3D Generation with Dual-mode Multi-view Latent Diffusioncited by 9
  7. 2025Wonder3D++: Cross-domain Diffusion for High-fidelity 3D Generation from a Single Imagecited by 8
  8. 2024PlacidDreamer: Advancing Harmony in Text-to-3D Generationcited by 6
  9. 2024Direct and Explicit 3D Generation from a Single Imagecited by 6
  10. 2025DMS:Diffusion-Based Multi-Baseline Stereo Generation for Improving Self-Supervised Depth Estimationcited by 3
  11. 2025Few-step Flow for 3D Generation via Marginal-Data Transport Distillationcited by 2
  12. 2025MVRoom: Controllable 3D Indoor Scene Generation with Multi-View Diffusion Modelscited by 1
  13. 2024Generative AI for Accessible and Inclusive Extended Realitycited by 0
  14. 2025ESCT3D: Efficient and Selectively Controllable Text-Driven 3D Content Generation with Gaussian Splattingcited by 0
  15. 2025LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Frameworkcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance
  2. 2024Text-to-3D Generation by 2D Editing
  3. 2024Flow Score Distillation for Diverse Text-to-3D Generation
  4. 2023Learn to Optimize Denoising Scores for 3D Generation: A Unified and Improved Diffusion Prior on NeRF and 3D Gaussian Splatting
  5. 2024Diffusion2: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models
  6. 2023DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation
  7. 2024Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle
  8. 2025Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data