Aether: Geometric-Aware Unified World Modeling
On the map: World models → Embodied and robot world models
also in 1 more
Abstract (arXiv)
The integration of geometric reconstruction and generative modeling remains a critical challenge in developing AI systems capable of human-like spatial reasoning. This paper proposes Aether, a unified framework that enables geometry-aware reasoning in world models by jointly optimizing three core capabilities: (1) 4D dynamic reconstruction, (2) action-conditioned video prediction, and (3) goal-conditioned visual planning. Through task-interleaved feature learning, Aether achieves synergistic knowledge sharing across reconstruction, prediction, and planning objectives. Building upon video generation models, our framework demonstrates zero-shot synthetic-to-real generalization despite never observing real-world data during training. Furthermore, our approach achieves zero-shot generalization in both action following and reconstruction tasks, thanks to its intrinsic geometric modeling. Notably, even without real-world data, its reconstruction performance is comparable with or even better than that of domain-specific models. Additionally, Aether employs camera trajectories as geometry-informed action spaces, enabling effective action-conditioned prediction and visual planning. We hope our work inspires the community to explore new frontiers in physically-reasonable world modeling and its applications.
Key facts. Cited by 97 papers in the map (data through 14 Oct 2026). Placed in Embodied and robot world models, one of 11 directions in World models. Builds on 63 of its 87 references that are in the map. First posted on arXiv 24 Mar 2025.
Builds on
63 of 87 references.
References · 63
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- 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 404
- 2024Pyramidal Flow Matching for Efficient Video Generative Modelingcited by 366
- 2023RoMa: Robust Dense Feature Matchingcited by 302
- 2024Diffusion for World Modeling: Visual Details Matter in Ataricited by 300
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- 20243D Reconstruction with Spatial Memorycited by 277
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- 2023Visual Geometry Grounded Deep Structure From Motioncited by 227
- 2024Global Structure-from-Motion Revisitedcited by 218
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- 2019ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residualscited by 181
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- 2024CAT4D: Create Anything in 4D with Multi-View Video Diffusion Modelscited by 161
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- 2024Learning Temporally Consistent Video Depth from Video Diffusion Priorscited by 100
50 most cited of 63 All 63 (JSON)
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Citing papers per year: 2025: 42; 2026: 55.
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- 2025Controllable Video Generation: A Surveycited by 98
- 2025Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modelingcited by 96
- 2025TesserAct: Learning 4D Embodied World Modelscited by 94
- 2025A Comprehensive Survey on World Models for Embodied AIcited by 68
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- 2026Action Images: End-to-End Policy Learning via Multiview Video Generationcited by 12
- 2025How Much 3D Do Video Foundation Models Encode?cited by 11
- 2026Prisma-World: Camera-Controllable Multi-Agent Video World Modelcited by 11
- 2026ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modelingcited by 10
- 2025HERO: Hierarchical Extrapolation and Refresh for Efficient World Modelscited by 9
- 2026UniSH: Unifying Scene and Human Reconstruction in a Feed-Forward Passcited by 9
- 2025VGGT-X: When VGGT Meets Dense Novel View Synthesiscited by 8
- 2026MeMix: Writing Less, Remembering More for Streaming 3D Reconstructioncited by 8
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- 2026Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trendscited by 8
- 2025E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Modelscited by 7
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- 2026AMB3R-SLAM: Kilometer-scale SLAM with Hierarchical Backend17 Sep 2026
- 2026PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control15 Sep 2026
- 2026Toward Unified Robot Learning: Bridging Representation, Vision-Language-Action, and World Models3 Sep 2026
- 2026OctWorld: Long-Range World-Consistent Video Generation with Octree-Based 3D Mapping3 Sep 2026
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- 2026SSR: A Training-Free Approach for Streaming 3D Reconstruction16 Mar 2026
- 2026Out of Sight, Out of Mind? Evaluating State Evolution in Video World Models13 Mar 2026
- 2026VGGT-World: Transforming VGGT into an Autoregressive Geometry World Model13 Mar 2026
- 2026WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching6 Mar 2026
- 2026ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling3 Mar 2026
- 2026Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels3 Mar 2026
- 2026WorldStereo: Bridging Camera-Guided Video Generation and Scene Reconstruction via 3D Geometric Memories2 Mar 2026
- 2026RnG: A Unified Transformer for Complete 3D Modeling from Partial Observations1 Mar 2026
- 2026SemanticNVS: Improving Semantic Scene Understanding in Generative Novel View Synthesis23 Feb 2026
- 2026VideoWorld 2: Learning Transferable Knowledge from Real-world Videos10 Feb 2026
- 2026MotionCrafter: Dense Geometry and Motion Reconstruction with a 4D VAE9 Feb 2026
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- 2026GigaWorld-Policy: An Efficient Action-Centered World--Action Modelcited by 139
- 2025Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modelingcited by 96
- 2025TesserAct: Learning 4D Embodied World Modelscited by 94
- 2025A Comprehensive Survey on World Models for Embodied AIcited by 68
- 2025OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modelingcited by 62
- 2026SANA-WM: Efficient Minute-Scale World Modeling with Hybrid Linear Diffusion Transformercited by 55
- 2025A Survey: Learning Embodied Intelligence from Physical Simulators and World Modelscited by 51
- 2025MindJourney: Test-Time Scaling with World Models for Spatial Reasoningcited by 50
- 2025DeepVerse: 4D Autoregressive Video Generation as a World Modelcited by 40
- 2025RoboScape: Physics-informed Embodied World Modelcited by 40
- 2025VRAG: Learning World Models for Interactive Video Generationcited by 38
- 2026VerseCrafter: Dynamic Realistic Video World Model with 4D Geometric Controlcited by 28
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- 2026OneLA: Learning Many Worlds from Latent Actions14 Oct 2026
- 2026SceneAE: Scene Generation and Reconstruction in Queryable 3D-Anchored Latent Space14 Oct 2026
- 20264LC: 4D Latent Cache for Efficient Conditioning in Dynamic World Modeling13 Oct 2026
- 2026SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching2 Oct 2026
- 20264Director: Controlling Video World Models with Rigid 3D Geometry1 Oct 2026
- 2026Code Plans, Diffusion Renders: Open-Ended Generative World Modeling22 Sep 2026
- 2026Toward Unified Robot Learning: Bridging Representation, Vision-Language-Action, and World Models3 Sep 2026
- 2026Quo Vadis, World Modeling?3 Aug 2026
- 2026Robot-Factored World Models via Robot Rendering24 Jul 2026
- 2026Reinforcement Learning: From Algorithms To Foundation Models20 Jul 2026
- 2026Pondering the Way: Spatial-perceiving World Action Model for Embodied Navigation29 Jun 2026
- 2026Prisma-World: Camera-Controllable Multi-Agent Video World Model8 Jun 2026
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- 2025Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstructioncited by 67
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- 2025Diff4Splat: Controllable 4D Scene Generation with Latent Dynamic Reconstruction Modelscited by 7
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- 2026DeblurNVS: Geometric Latent Diffusion for Novel View Synthesis from Sparse Motion-Blurred Images31 May 2026
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- 2026WorldStereo: Bridging Camera-Guided Video Generation and Scene Reconstruction via 3D Geometric Memories2 Mar 2026
- 2026SemanticNVS: Improving Semantic Scene Understanding in Generative Novel View Synthesis23 Feb 2026
- 2026Gen3R: 3D Scene Generation Meets Feed-Forward Reconstruction7 Jan 2026
- 2025Diff4Splat: Controllable 4D Scene Generation with Latent Dynamic Reconstruction Models1 Nov 2025
- 2025Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstruction10 Apr 2025
- 2025π3: Permutation-Equivariant Visual Geometry Learningcited by 319
- 2025ViPE: Video Pose Engine for 3D Geometric Perceptioncited by 170
- 2025TTT3R: 3D Reconstruction as Test-Time Trainingcited by 129
- 2025Controllable Video Generation: A Surveycited by 98
- 2025SceneGen: Single-Image 3D Scene Generation in One Feedforward Passcited by 54
- 2025CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learningcited by 40
- 2025WinT3R: Window-Based Streaming Reconstruction with Camera Token Poolcited by 35
- 2025Advances in Feed-Forward 3D Reconstruction and View Synthesis: A Surveycited by 27
- 2025PlayerOne: Egocentric World Simulatorcited by 20
- 2025AMB3R: Accurate Feed-forward Metric-scale 3D Reconstruction with Backendcited by 20
- 2025iTACO: Interactable Digital Twins of Articulated Objects from Casually Captured RGBD Videoscited by 19
- 2025Reconstructing 4D Spatial Intelligence: A Surveycited by 14
12 most cited of 38 All 38 (JSON)
- 2026Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Them28 Sep 2026
- 2026AMB3R-SLAM: Kilometer-scale SLAM with Hierarchical Backend17 Sep 2026
- 2026PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control15 Sep 2026
- 2026FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors24 Aug 2026
- 2026SceneConductor: 3D Scene Generation from a Single Image with Multi-Agent Orchestration7 Jun 2026
- 2026Which Pretraining Paradigm Better Serves Spatial Intelligence? An Empirical Comparison of Vision-Language and Video Generation Models27 May 2026
- 2026Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation5 May 2026
- 2026RayMap3R: Inference-Time RayMap for Dynamic 3D Reconstruction21 Mar 2026
- 2026OneWorld: Taming Scene Generation with 3D Unified Representation Autoencoder17 Mar 2026
- 2026MeMix: Writing Less, Remembering More for Streaming 3D Reconstruction16 Mar 2026
- 2026SSR: A Training-Free Approach for Streaming 3D Reconstruction16 Mar 2026
- 2026Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels3 Mar 2026
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