LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching
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Cited by 93 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios. While recent advancements in text-to-3D generation have shown promise, they often fall short in rendering detailed and high-quality 3D models. This problem is especially prevalent as many methods base themselves on Score Distillation Sampling (SDS). This paper identifies a notable deficiency in SDS, that it brings inconsistent and low-quality updating direction for the 3D model, causing the over-smoothing effect. To address this, we propose a novel approach called Interval Score Matching (ISM). ISM employs deterministic diffusing trajectories and utilizes interval-based score matching to counteract over-smoothing. Furthermore, we incorporate 3D Gaussian Splatting into our text-to-3D generation pipeline. Extensive experiments show that our model largely outperforms the state-of-the-art in quality and training efficiency.
Key facts. Cited by 290 papers in the map (data through 7 Oct 2026). Builds on 39 of its 50 references that are in the map. First posted on arXiv 19 Nov 2023.
Builds on
39 of 50 references.
References · 39
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
- 2020Denoising Diffusion Implicit Modelscited by 9,655
- 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
- 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
- 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
- 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
- 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
27 more
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- 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
- 2023MVDream: Multi-view Diffusion for 3D Generationcited by 928
- 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 837
- 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
- 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 684
- 2018DensePose: Dense Human Pose Estimation In The Wildcited by 573
- 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 569
- 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
- 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
- 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
- 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
- 2023Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priorscited by 395
- 2021Text2Mesh: Text-Driven Neural Stylization for Meshescited by 332
- 2023Text-to-3D using Gaussian Splattingcited by 299
- 2023Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Modelscited by 232
- 2022Diffusion models as plug-and-play priorscited by 230
- 2022Dual Diffusion Implicit Bridges for Image-to-Image Translationcited by 212
- 2023DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Modelscited by 154
- 2023Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyondcited by 139
- 2023Text-to-3D with Classifier Score Distillationcited by 127
- 2023Noise-Free Score Distillationcited by 99
- 2023DreamWaltz: Make a Scene with Complex 3D Animatable Avatarscited by 82
- 2023Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflectioncited by 68
- 2023Consistent123: One Image to Highly Consistent 3D Asset Using Case-Aware Diffusion Priorscited by 64
- 2023AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Posecited by 60
- 2023ConRad: Image Constrained Radiance Fields for 3D Generation from a Single Imagecited by 5
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Citing papers per year: 2023: 4; 2024: 125; 2025: 110; 2026: 51.
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