Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
Real-world applications like video gaming and virtual reality often demand the ability to model 3D scenes that users can explore along custom camera trajectories. While significant progress has been made in generating 3D objects from text or images, creating long-range, 3D-consistent, explorable 3D scenes remains a complex and challenging problem. In this work, we present Voyager, a novel video diffusion framework that generates world-consistent 3D point-cloud sequences from a single image with user-defined camera path. Unlike existing approaches, Voyager achieves end-to-end scene generation and reconstruction with inherent consistency across frames, eliminating the need for 3D reconstruction pipelines (e.g., structure-from-motion or multi-view stereo). Our method integrates three key components: 1) World-Consistent Video Diffusion: A unified architecture that jointly generates aligned RGB and depth video sequences, conditioned on existing world observation to ensure global coherence 2) Long-Range World Exploration: An efficient world cache with point culling and an auto-regressive inference with smooth video sampling for iterative scene extension with context-aware consistency, and 3) Scalable Data Engine: A video reconstruction pipeline that automates camera pose estimation and metric depth prediction for arbitrary videos, enabling large-scale, diverse training data curation without manual 3D annotations. Collectively, these designs result in a clear improvement over existing methods in visual quality and geometric accuracy, with versatile applications.
Key facts. Cited by 101 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 36 of its 53 references that are in the map. First posted on arXiv 4 Jun 2025.
Builds on
36 of 53 references.
Closest ancestors · 7
Same direction, newest first
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- 2024CAT3D: Create Anything in 3D with Multi-View Diffusion Models16 May
- 2023ReconFusion: 3D Reconstruction with Diffusion Priors5 Dec
- 2023Zero-1-to-3: Zero-shot One Image to 3D Object20 Mar
Other references · 29
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- 2021DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Camerascited by 687
- 2023Language Model Beats Diffusion -- Tokenizer is Key to Visual Generationcited by 640
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- 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 395
- 2022Latent Video Diffusion Models for High-Fidelity Long Video Generationcited by 388
- 2025GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Controlcited by 341
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- 2025ReCamMaster: Camera-Controlled Generative Rendering from A Single Videocited by 287
- 2024StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Textcited by 251
- 2023LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenescited by 231
- 2024WonderWorld: Interactive 3D Scene Generation from a Single Imagecited by 202
- 2023NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generationcited by 171
- 2023Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoisingcited by 139
- 2024FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attentioncited by 89
- 2025VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Controlcited by 84
- 2024EasyAnimate: High-Performance Video Generation Framework with Hybrid Windows Attention and Reward Backpropagationcited by 77
- 2023DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Videocited by 74
- 2024GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warpingcited by 73
- 2024Allegro: Open the Black Box of Commercial-Level Video Generation Modelcited by 70
- 2025FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesiscited by 37
- 2025A Recipe for Generating 3D Worlds From a Single Imagecited by 13
- 2024Toon3D: Seeing Cartoons from New Perspectivescited by 3
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Citing papers per year: 2025: 30; 2026: 71.
101 papers.
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- 20264DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans30 Jul 2026
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- 2026MetaView: Monocular Novel View Synthesis with Scale-Aware Implicit Geometry Priors13 Jul 2026
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- 2026Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video14 May 2026
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- 2026Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion17 Apr 2026
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