worldbench/awesome-3d-4d-world-models
🌐 3D and 4D World Modeling: A Survey
😎 Awesome 3D and 4D World Models
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This survey reviews state-of-the-art 3D and 4D world models - systems that learn, predict, and simulate the geometry and dynamics of real environments from multi-modal signals.
We unify terminology, scope, and evaluations, and organize the space into three complementary paradigms by representation:
For more details, kindly refer to our paper and project page. 🚀
📚 Citation
If you find this work helpful for your research, please kindly consider citing our papers:
@article{survey_3d_4d_world_models,
title = {{3D} and {4D} World Modeling: A Survey},
author = {Lingdong Kong and Wesley Yang and Jianbiao Mei and Youquan Liu and Ao Liang and Dekai Zhu and Dongyue Lu and Wei Yin and Xiaotao Hu and Mingkai Jia and Junyuan Deng and Kaiwen Zhang and Yang Wu and Tianyi Yan and Shenyuan Gao and Song Wang and Linfeng Li and Liang Pan and Yong Liu and Jianke Zhu and Wei Tsang Ooi and Steven C. H. Hoi and Ziwei Liu},
journal = {arXiv preprint arXiv:2509.07996},
year = {2025}
}@article{worldlens,
title = {{WorldLens}: Full-Spectrum Evaluations of Driving World Models in Real World},
author = {Ao Liang and Lingdong Kong and Tianyi Yan and Hongsi Liu and Wesley Yang and Ziqi Huang and Wei Yin and Jialong Zuo and Yixuan Hu and Dekai Zhu and Dongyue Lu and Youquan Liu and Guangfeng Jiang and Linfeng Li and Xiangtai Li and Long Zhuo and Lai Xing Ng and Benoit R. Cottereau and Changxin Gao and Liang Pan and Wei Tsang Ooi and Ziwei Liu},
journal = {arXiv preprint arXiv:2512.10958},
year = {2025}
}Table of Contents
- 0. Background
- 1. Benchmarks & Datasets
- 2. World Modeling from Video Generation
- 3. World Modeling from Occupancy Generation
- 4. World Modeling from LiDAR Generation
- 5. Applications
- 6. Other Resources
- 7. Acknowledgements
Background
What Are Native 3D Representations?
Unlike 2D projections, native 3D/4D signals directly encode metric geometry, visibility, and motion in the physical coordinates where agents act. Examples include:
- RGB-D imagery (2D images with depth channels)
- Occupancy grids (voxelized maps of free vs. occupied space)
- LiDAR point clouds (3D coordinates from active sensing)
- Neural fields (e.g., NeRF, Gaussian Splatting)
What Are World Models in 3D and 4D?
A 3D/4D world model is an internal representation that allows an agent to imagine, forecast, and interact with its environment in the 3D space.
Together, these models provide the foundation for simulation, planning, and embodied intelligence in complex environments.
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1. Benchmarks & Datasets
Benchmarks
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|---|---|---|
| WorldLens | VBench | WorldScore |
Workshops
| Theme | Venue | Date | Location | Recording |
|---|---|---|---|---|
| Workshop on 4D World Models: Bridging Generation and Reconstruction | CVPR 2026 | TBD | Denver | - |
| The 2nd Workshop on World Models | ICLR 2026 | April 23, 2026 | Rio de Janeiro | - |
| Workshop on World Modeling | - | February 4-6, 2026 | Montréal | - |
| Workshop on Embodied World Models for Decision Making | NeurIPS 2025 | December 6, 2025 | San Diego | - |
| Workshop on Reliable and Interactable World Models: Geometry, Physics, Interactivity and Real-World Generalization | ICCV 2025 | October 19, 2025 | Hawai'i | - |
| Workshop on Building Physically Plausible World Models | ICML 2025 | July 19, 2025 | Vancouver | - |
| Workshop on Assessing World Models | ICML 2025 | July 18, 2025 | Vancouver | - |
| Workshop on Benchmarking World Models | CVPR 2025 | June 12, 2025 | Nashville | - |
| Workshop on World Models: Understanding, Modelling and Scaling | ICLR 2025 | April 28, 2025 | Singapore | - |
| Workshop on Foundation Models for Autonomous Systems | CVPR 2024 | June 17, 2025 | Seattle | [YouTube] |
Datasets
⏲️ In chronological order, from the earliest to the latest.
2. World Modeling from Video Generation
1️⃣ Data Engines
⏲️ In chronological order, from the earliest to the latest.
2️⃣ Action Interpreters
⏲️ In chronological order, from the earliest to the latest.
3️⃣ Neural Simulators
⏲️ In chronological order, from the earliest to the latest.
4️⃣ Scene Reconstructors
⏲️ In chronological order, from the earliest to the latest.
3. World Modeling from Occupancy Generation
1️⃣ Scene Representors
⏲️ In chronological order, from the earliest to the latest.
2️⃣ Occupancy Forecasters
⏲️ In chronological order, from the earliest to the latest.
3️⃣ Autoregressive Simulators
⏲️ In chronological order, from the earliest to the latest.
4. World Modeling from LiDAR Generation
1️⃣ Data Engines
⏲️ In chronological order, from the earliest to the latest.
2️⃣ Action Forecasters
⏲️ In chronological order, from the earliest to the latest.
3️⃣ Autoregressive Simulators
⏲️ In chronological order, from the earliest to the latest.
5. Applications
1️⃣ Autonomous Driving
2️⃣ Robotics
3️⃣ Video Games & XR
4️⃣ Digital Twins
5️⃣ Other Topics
| Model | Paper | Venue | Website | GitHub |
|---|---|---|---|---|
| - | Interpreting Physics in Video World Models |
arXiv 2026 | - | - |





