---
task_categories:
- robotics
- image-text-to-text
license: other
---

# MUSON: A Reasoning-oriented Multimodal Dataset for Socially Compliant Navigation

[Paper](https://huggingface.co/papers/2512.22867) | [GitHub](https://github.com/MUSON-dataset/MUSON)

## Overview

MUSON is a reasoning-oriented multimodal dataset designed for short-horizon socially compliant navigation in urban environments. It contains 10,110 egocentric samples collected across diverse indoor and outdoor social scenes.

## Dataset Structure

After downloading and extracting the dataset package, the dataset is organized as follows:

```text
MUSON/
├── MUSON_images/
│   ├── 000001.jpg
│   ├── 000002.jpg
│   └── ...
└── MUSON_Annotations.json
```

- `MUSON_images/`: RGB images
- `MUSON_Annotations.json`: Structured 5-step reasoning annotations

Each annotation contains:
- **perception**: Static physical constraints and pedestrian visual attributes.
- **prediction**: Anticipated pedestrian movements.
- **reasoning**: Social norm compliance assessment.
- **action**: Standardized action output chosen from a six-action decision space.
- **explanation**: Natural language justification for the decision.

## Citation

If you use this dataset, please cite:

```bibtex
@article{liu2025muson,
  title={MUSON: A Reasoning-oriented Multimodal Dataset for Socially Compliant Navigation in Urban Environments},
  author={Liu, Zhuonan and Zhang, Xinyu and Wang, Zishuo and Kawabata, Tomohito and Xiao, Xuesu and Xiao, Ling},
  journal={arXiv preprint arXiv:2512.22867},
  year={2025}
}
```

## License

Research use only.