Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
Text-guided diffusion models have revolutionized image and video generation and have also been successfully used for optimization-based 3D object synthesis. Here, we instead focus on the underexplored text-to-4D setting and synthesize dynamic, animated 3D objects using score distillation methods with an additional temporal dimension. Compared to previous work, we pursue a novel compositional generation-based approach, and combine text-to-image, text-to-video, and 3D-aware multiview diffusion models to provide feedback during 4D object optimization, thereby simultaneously enforcing temporal consistency, high-quality visual appearance and realistic geometry. Our method, called Align Your Gaussians (AYG), leverages dynamic 3D Gaussian Splatting with deformation fields as 4D representation. Crucial to AYG is a novel method to regularize the distribution of the moving 3D Gaussians and thereby stabilize the optimization and induce motion. We also propose a motion amplification mechanism as well as a new autoregressive synthesis scheme to generate and combine multiple 4D sequences for longer generation. These techniques allow us to synthesize vivid dynamic scenes, outperform previous work qualitatively and quantitatively and achieve state-of-the-art text-to-4D performance. Due to the Gaussian 4D representation, different 4D animations can be seamlessly combined, as we demonstrate. AYG opens up promising avenues for animation, simulation and digital content creation as well as synthetic data generation.
Key facts. Cited by 169 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 100 of its 115 references that are in the map. First posted on arXiv 21 Dec 2023.
Builds on
100 of 115 references.
Closest ancestors · 29
Same direction, newest first
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- 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Image7 Sep
- 2023MVDream: Multi-view Diffusion for 3D Generation31 Aug
- 2023IT3D: Improved Text-to-3D Generation with Explicit View Synthesis22 Aug
17 more
- 2023Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors30 Jun
- 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation25 May
- 2023TextMesh: Generation of Realistic 3D Meshes From Text Prompts24 Apr
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- 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation24 Mar
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- 2022TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape Generation23 Nov
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- 2022LION: Latent Point Diffusion Models for 3D Shape Generation12 Oct
- 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep
- 2021Diffusion Probabilistic Models for 3D Point Cloud Generation2 Mar
Other references · 71
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- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
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- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
- 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,778
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- 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,198
- 2021Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrievalcited by 1,177
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- 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 931
- 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
- 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
- 2023Objaverse-XL: A Universe of 10M+ 3D Objectscited by 774
- 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 759
- 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 737
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- 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
- 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
- 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
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- 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 471
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- 2023PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamicscited by 377
- 2022PhysDiff: Physics-Guided Human Motion Diffusion Modelcited by 368
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- 2023LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matchingcited by 290
- 2023Preserve Your Own Correlation: A Noise Prior for Video Diffusion Modelscited by 285
- 2023Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystackcited by 279
- 2023Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioningcited by 255
- 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
50 most cited of 71 All 71 (JSON)
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Citing papers per year: 2023: 1; 2024: 82; 2025: 59; 2026: 27.
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