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license: apache-2.0
size_categories:
- 100K<n<1M
task_categories:
- image-to-video
tags:
- robotics
- world-models
---
# MultiWorld Dataset
## Dataset Summary
**MultiWorld** is a large-scale multi-agent multi-view video dataset collected for training video world models. It contains two complementary sources of data:
1. **It Takes Two Gameplay Dataset**: 100+ hours of real human gameplay from the cooperative action-adventure game *It Takes Two*, featuring dual-agent synchronized actions with distinct first-person viewpoints.
2. **RoboFactory Manipulation Dataset**: Multi-robot manipulation trajectories spanning 4 tasks with 2-4 agents and variable camera viewpoints, including both success and failure episodes.
This dataset is the official release accompanying the paper [MultiWorld: Scalable Multi-Agent Multi-View Video World Models](https://huggingface.co/papers/2604.18564).
- **Homepage:** https://multi-world.github.io
- **Repository:** https://github.com/CIntellifusion/MultiWorld
- **Paper:** [arXiv:2604.18564](https://huggingface.co/papers/2604.18564)
---
## Sample Usage
### Dataset Download
You can download the dataset using the Hugging Face CLI:
```bash
hf auth login
hf download Haoyuwu/MultiWorldData --repo-type dataset \
--local-dir ./data
bash preprocess/untar_chunks.sh
```
After running `preprocess/untar_chunks.sh`, the archives are extracted to:
- `data/ittakestwo_release/` — It Takes Two dataset
- `data/robots_release/` — Robotics dataset
---
## Dataset Details
### It Takes Two Gameplay
| Property | Value |
|----------|-------|
| **Total Duration** | 100+ hours |
| **Frame Rate** | 60 FPS |
| **Resolution** | 480 × 960 |
| **Agents** | 2 players |
| **Viewpoints** | 2 distinct first-person views per episode |
| **Actions** | Synchronized keyboard and mouse actions per agent |
| **Modality** | RGB video + discrete/continuous action vectors |
The gameplay videos are captured from real human players cooperating in the game. Each frame is accompanied by per-agent action labels capturing keyboard presses and mouse movements.
### RoboFactory Manipulation
| Property | Value |
|----------|-------|
| **Tasks** | 4 multi-robot manipulation tasks |
| **Agents** | 2–4 robots per task |
| **Viewpoints** | Variable camera configurations per task |
| **Resolution** | 256 × 320 |
| **Success Episodes** | 1,000 per task |
| **Failure Episodes** | 2,000 per task |
| **Modality** | RGB video + robot proprioception + actions |
Tasks include collaborative stacking, pushing, and pick-and-place scenarios. Both successful and failed trajectories are included to support learning robust world models and failure prediction.
---
### Possible Usage
The dataset is intended for research in:
- Video world models
- Multi-agent video generation
- Multi-view consistent video generation.
---
### Contact
For questions about the dataset, please open an issue on the [GitHub repository](https://github.com/CIntellifusion/MultiWorld) or contact the authors.
## Citation
```bibtex
@article{wu2025multiworld,
title={MultiWorld: Scalable Multi-Agent Multi-View Video World Models},
author={Wu, Haoyu and Yu, Jiwen and Zou, Yingtian and Liu, Xihui},
journal={arXiv preprint arXiv:2604.18564},
year={2026}
}
``` |