mlsanityData to 7 Oct 2026

AutoScape: Geometry-Consistent Long-Horizon Scene Generation

arXiv 2510.20726 ↗First posted 23 Oct 2025cs.CVcited by 2

On the map: Diffusion models → Diffusion and flow policies for robotics

Abstract (arXiv)

This paper proposes AutoScape, a long-horizon driving scene generation framework. At its core is a novel RGB-D diffusion model that iteratively generates sparse, geometrically consistent keyframes, serving as reliable anchors for the scene's appearance and geometry. To maintain long-range geometric consistency, the model 1) jointly handles image and depth in a shared latent space, 2) explicitly conditions on the existing scene geometry (i.e., rendered point clouds) from previously generated keyframes, and 3) steers the sampling process with a warp-consistent guidance. Given high-quality RGB-D keyframes, a video diffusion model then interpolates between them to produce dense and coherent video frames. AutoScape generates realistic and geometrically consistent driving videos of over 20 seconds, improving the long-horizon FID and FVD scores over the prior state-of-the-art by 48.6% and 43.0%, respectively.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 86 of its 91 references that are in the map. First posted on arXiv 23 Oct 2025.

Builds on

86 of 91 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles19 Dec
  2. 2024MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control21 Nov
  3. 2024Streetscapes: Large-scale Consistent Street View Generation Using Autoregressive Video Diffusion18 Jul
  4. 2023Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion2 Nov
  5. 2023MagicDrive: Street View Generation with Diverse 3D Geometry Control4 Oct

Other references · 81

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  7. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  8. 2023Segment Anythingcited by 8,158
  9. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  10. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  11. 2022Classifier-Free Diffusion Guidancecited by 5,717
  12. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
38 more
  1. 2022Flow Matching for Generative Modelingcited by 5,426
  2. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  3. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
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  5. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
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  7. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
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  12. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
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  14. 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,204
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  16. 2022MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Modelcited by 768
  17. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 734
  18. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 701
  19. 2023VILA: On Pre-training for Visual Language Modelscited by 686
  20. 2023GAIA-1: A Generative World Model for Autonomous Drivingcited by 618
  21. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 552
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  28. 2022SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generationcited by 287
  29. 2021HDMapNet: An Online HD Map Construction and Evaluation Frameworkcited by 280
  30. 2025ReCamMaster: Camera-Controlled Generative Rendering from A Single Videocited by 278
  31. 2023DriveDreamer: Towards Real-world-driven World Models for Autonomous Drivingcited by 258
  32. 2023Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Modelscited by 245
  33. 2024Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splattingcited by 218
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  38. 2025GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Drivingcited by 178

50 most cited of 81 All 81 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

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Close in wording, no citation either way

  1. 2025DriveGen3D: Boosting Feed-Forward Driving Scene Generation with Efficient Video Diffusion
  2. 2025VideoFrom3D: 3D Scene Video Generation via Complementary Image and Video Diffusion Models
  3. 2023DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model
  4. 2025X-Scene: Large-Scale Driving Scene Generation with High Fidelity and Flexible Controllability
  5. 2026SEM-ROVER: Semantic Voxel-Guided Diffusion for Large-Scale Driving Scene Generation
  6. 2025WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion
  7. 2024V3D: Video Diffusion Models are Effective 3D Generators
  8. 2024Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Models