# EvHumanMotion

[Dataset on HuggingFace 🤗](https://huggingface.co/datasets/potentialming/EvHumanMotion)

**EvHumanMotion** is a real-world dataset captured using the DAVIS346 event camera, focusing on human motion under diverse and challenging scenarios. It is designed to support event-driven human animation research, especially under motion blur, low-light, and overexposure conditions. This dataset was introduced in the [EvAnimate](https://arxiv.org/abs/2503.18552) paper.

## Dataset Structure

The dataset is organized into two main parts:

- **EvHumanMotion_aedat4**: Raw event streams in `.aedat4` format.
- **EvHumanMotion_frame**: Frame-level event slices and RGB frames.

Each is categorized into:
- `indoor_day/`
- `indoor_night_high_noise/`
- `indoor_night_low_noise/`
- `outdoor_day/`
- `outdoor_night/`

Each environment contains four scenarios:
- `low_light/`
- `motion_blur/`
- `normal/`
- `over_exposure/`

Example path:

```
EvHumanMotion_frame/indoor_day/low_light/dvSave-2025_03_04_13_02_53/
├── event_frames/
│   ├── events_0000013494.png
│   └── ...
└── frames/
    ├── frames_1741064573617350.png
    └── ...
```

## Features

- **Total sequences**: 113
- **Participants**: 20 (10 male, 10 female)
- **Duration**: ~10 seconds per video
- **Frame rate**: 24 fps
- **Scenarios**: Normal, Motion Blur, Overexposure, Low Light
- **Modalities**: RGB + Event data (both `.aedat4` and frame-level)

## Applications

This dataset supports:
- Event-to-video generation
- Human animation in extreme conditions
- Motion transfer with high temporal resolution

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("potentialming/EvHumanMotion")
```

## License

Apache 2.0 License

## Citation

If you use this dataset, please cite:

```bibtex
@article{qu2025evanimate,
  title={EvAnimate: Event-conditioned Image-to-Video Generation for Human Animation},
  author={Qu, Qiang and Li, Ming and Chen, Xiaoming and Liu, Tongliang},
  journal={arXiv preprint arXiv:2503.18552},
  year={2025}
}
```

## Contact

Dataset maintained by [Ming Li](https://huggingface.co/potentialming).