---
license: cc-by-nc-sa-4.0
language:
- en
- de
- vi
- gsw
tags:
- video
- audio
- speech
- image
- 6dof
size_categories:
- n>1T
pretty_name: 'The CASTLE 2024 Dataset: Advancing the Art of Multimodal Understanding'
---

# What is CASTLE?

![image](https://cdn-uploads.huggingface.co/production/uploads/6304ed5e34c824b1724ff2cd/kBKG4r4dkBztwtwLrAosY.png)

The CASTLE dataset is a large-scale, multimodal dataset designed for advancing research in lifelogging, human activity recognition, and multimodal retrieval. It provides a rich collection of time-aligned sensor and video data for analysis and benchmarking. See the [Paper](https://doi.org/10.1145/3746027.3758199) (or its [arXiv pre-print](https://arxiv.org/abs/2503.17116)) for more details.

You can check our [website](https://castle-dataset.github.io/) for more details.

## Characteristics

* Captured over **four days** in a controlled environment
* **10 participants** engaged in natural activities
* **15 video streams** (10 egocentric, 5 static perspectives)
* Over **600 hours** of UHD 50fps video with audio
* Includes **6DoF IMU, GPS, and biometric data**
* **8.22TB** total size

## License

The CASTLE dataset is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

## Terms of Use

By downloading the dataset, you agree to the following terms:

* The dataset is provided for research purposes only.
* You will not use the dataset for any commercial purposes.
* You will not distribute the dataset or any derivative works to others.
* You will provide appropriate credit to the dataset authors in your publications.
If you are using the dataset in your research, please consider citing the following paper:

```bibtex
@inproceedings{10.1145/3746027.3758199,
  author = {Rossetto, Luca and Bailer, Werner and Dang-Nguyen, Duc-Tien and Healy, Graham and J\'{o}nsson, Bj\"{o}rn \TH{}\'{o}r and Kongmeesub, Onanong and Le, Hoang-Bao and Rudinac, Stevan and Sch\"{o}ffmann, Klaus and Spiess, Florian and Tran, Allie and Tran, Minh-Triet and Tran, Quang-Linh and Gurrin, Cathal},
  title = {The CASTLE 2024 Dataset: Advancing the Art of Multimodal Understanding},
  year = {2025},
  isbn = {9798400720352},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3746027.3758199},
  doi = {10.1145/3746027.3758199},
  booktitle = {Proceedings of the 33rd ACM International Conference on Multimedia},
  pages = {12629–12635},
  numpages = {7},
  keywords = {dataset, egocentric vision, lifelogging, multi-perspective video, multimodal understanding},
  location = {Dublin, Ireland},
  series = {MM '25}
}
```

# Challenges
We are organizing a series of challenges to encourage the research community to explore and utilize the CASTLE dataset.

To see the list of challenges and their details, please visit the [Challenges](https://castle-dataset.github.io/challenges/) page on the website.