Added README.md

README.md

@@ -1,3 +1,67 @@
----
-license: cc-by-nc-sa-4.0
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+---
+license: cc-by-nc-sa-4.0
+language:
+- en
+- de
+- vi
+tags:
+- video
+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.