| --- |
| 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? |
|
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|  |
|
|
| 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. |
