ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose ViewCrafter, a novel method for synthesizing high-fidelity novel views of generic scenes from single or sparse images with the prior of video diffusion model. Our method takes advantage of the powerful generation capabilities of video diffusion model and the coarse 3D clues offered by point-based representation to generate high-quality video frames with precise camera pose control. To further enlarge the generation range of novel views, we tailored an iterative view synthesis strategy together with a camera trajectory planning algorithm to progressively extend the 3D clues and the areas covered by the novel views. With ViewCrafter, we can facilitate various applications, such as immersive experiences with real-time rendering by efficiently optimizing a 3D-GS representation using the reconstructed 3D points and the generated novel views, and scene-level text-to-3D generation for more imaginative content creation. Extensive experiments on diverse datasets demonstrate the strong generalization capability and superior performance of our method in synthesizing high-fidelity and consistent novel views.
Key facts. Cited by 392 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 66 of its 78 references that are in the map. First posted on arXiv 3 Sep 2024.
Builds on
66 of 78 references.
Closest ancestors · 11
Same direction, newest first
- 2024MultiDiff: Consistent Novel View Synthesis from a Single Image26 Jun
- 2024CAT3D: Create Anything in 3D with Multi-View Diffusion Models16 May
- 2024RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion10 Apr
- 2023ReconFusion: 3D Reconstruction with Diffusion Priors5 Dec
- 2023DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior25 Oct
- 2023HiFi-123: Towards High-fidelity One Image to 3D Content Generation10 Oct
- 2023Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields19 May
- 2023Generative Novel View Synthesis with 3D-Aware Diffusion Models5 Apr
- 2023Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior24 Mar
- 2023Zero-1-to-3: Zero-shot One Image to 3D Object20 Mar
- 2022Novel View Synthesis with Diffusion Models6 Oct
Other references · 55
- 2017Attention Is All You Needcited by 59,932
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
- 2020Denoising Diffusion Implicit Modelscited by 9,655
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
- 2022Classifier-Free Diffusion Guidancecited by 5,717
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
- 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
38 more
- 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,526
- 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,574
- 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,526
- 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
- 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuningcited by 1,418
- 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,339
- 2024Grounding Image Matching in 3D with MASt3Rcited by 960
- 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 834
- 2020Accelerating 3D Deep Learning with PyTorch3Dcited by 781
- 2023GLIGEN: Open-Set Grounded Text-to-Image Generationcited by 774
- 2023pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstructioncited by 668
- 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 646
- 2023Structure and Content-Guided Video Synthesis with Diffusion Modelscited by 589
- 2023MotionCtrl: A Unified and Flexible Motion Controller for Video Generationcited by 568
- 2024MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Imagescited by 553
- 2023DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Visioncited by 514
- 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
- 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 463
- 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generationcited by 448
- 2019SynSin: End-to-end View Synthesis from a Single Imagecited by 364
- 2021Light Field Networks: Neural Scene Representations with Single-Evaluation Renderingcited by 330
- 2023FSGS: Real-Time Few-shot View Synthesis using Gaussian Splattingcited by 278
- 2020Single-View View Synthesis with Multiplane Imagescited by 263
- 2023DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectorycited by 260
- 2024DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalizationcited by 256
- 2023LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenescited by 228
- 2023MVImgNet: A Large-scale Dataset of Multi-view Imagescited by 219
- 20203D Photography using Context-aware Layered Depth Inpaintingcited by 206
- 2024CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generationcited by 163
- 2024VD3D: Taming Large Video Diffusion Transformers for 3D Camera Controlcited by 156
- 2023Make-Your-Video: Customized Video Generation Using Textual and Structural Guidancecited by 129
- 2021Geometry-Free View Synthesis: Transformers and no 3D Priorscited by 99
- 2024MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Modelcited by 87
- 2021PixelSynth: Generating a 3D-Consistent Experience from a Single Imagecited by 82
- 2024ToonCrafter: Generative Cartoon Interpolationcited by 68
- 2023Real-Time Radiance Fields for Single-Image Portrait View Synthesiscited by 64
- 2022Single-View View Synthesis in the Wild with Learned Adaptive Multiplane Imagescited by 59
- 2023NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Renderingcited by 53
50 most cited of 55 All 55 (JSON)
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Citing papers per year: 2024: 31; 2025: 179; 2026: 182.
392 papers.
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- 2026GenNVS: Geometry-enhanced Novel View Synthesis via Disentangled 3D Prior28 Sep 2026
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- 2026Sparse auto-regressive modeling for scene generation from multi-view images3 Sep 2026
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