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:
- 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.
- 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".
- Homepage: https://multi-world.github.io
- Repository: https://github.com/CIntellifusion/MultiWorld
- Paper: arXiv:XXXX.XXXXX
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 or contact the authors.
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