| --- |
| |
| |
| language: |
| - en |
| - zh |
| - fr |
| - ja |
| - es |
| license: cc-by-nc-sa-4.0 |
|
|
| tags: |
| - Multimedia |
| - Panoramic |
| - Video |
| - Multi-viewpoint |
|
|
| viewer: false |
| --- |
| |
| # <i>360+x</i> Dataset |
|
|
| For more information, please feel free to check our [project page](https://x360dataset.github.io/). |
|
|
| ## Overview |
|
|
| 360+x dataset introduces a unique panoptic perspective to scene understanding, differentiating itself from traditional |
| datasets by offering multiple viewpoints and modalities, captured from a variety of scenes |
|
|
| ### Key Features: |
|
|
| - **Multi-viewpoint Captures:** Includes 360° panoramic video, third-person front view video, egocentric monocular |
| video, and egocentric binocular video. |
| - **Rich Audio Modalities:** Features normal audio and directional binaural delay. |
| - **2,152 multi-model videos** captured by 360 cameras and Spectacles camera (8579k frames in total) Captured in 17 |
| cities across 5 countries, covering 28 scenes ranging from Artistic Spaces to Natural Landscapes. |
| - **Action Temporal Segmentation:** Provides labels for 38 action instances for each video pair. |
|
|
| ## Download This Repo |
|
|
| You can use the following code to download the entire dataset: |
| ``` |
| from huggingface_hub import snapshot_download |
| |
| repo_id = "quchenyuan/360x_dataset" |
| |
| snapshot_download(repo_id=repo_id, repo_type="dataset", token={your_token}) |
| ``` |
|
|
| ## Dataset Details |
|
|
| ### Project Description |
|
|
| - **Developed by:** Hao Chen, Yuqi Hou, Chenyuan Qu, Irene Testini, Xiaohan Hong, Jianbo Jiao |
| - **Funded by:** the Ramsay Research Fund, and the Royal Society Short Industry Fellowship |
| - **License:** Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
|
|
| ### Sources |
| - **Repository:** Coming Soon |
| - **Paper:** https://arxiv.org/abs/2404.00989 |
|
|
| ## Dataset Statistics |
|
|
| - **Total Videos:** 2,152, split between 464 videos captured using 360 cameras and 1,688 with Spectacles cameras. |
| - **Scenes:** 15 indoor and 13 outdoor, totalling 28 scene categories. |
| - **Short Clips:** The videos have been segmented into 1,380 shorter clips, each approximately 10 seconds long, totalling |
| around 67.78 hours. |
| - **Frames:** 8,579k frames across all clips. |
|
|
| ## Dataset Structure |
|
|
| Our dataset offers a comprehensive collection of panoramic videos, binocular videos, and third-person videos, each pair |
| of videos accompanied by annotations. Additionally, it includes features extracted using I3D, VGGish, and ResNet-18. |
| Given the high-resolution nature of our dataset (5760x2880 for panoramic and binocular videos, 1920x1080 for |
| third-person front view videos), the overall size is considerably large. To accommodate diverse research needs and |
| computational resources, we also provide a lower-resolution version of the dataset (5760x2880 for panoramic， 2432x1216 binocular |
| videos, and 1920x1080 for third-person front view videos) available for download. |
|
|
| <b>In this repo, we provide the lower-resolution version of the dataset. To access the high-resolution version, please |
| visit the <a href="https://x360dataset.github.io/">official website</a>.</b> |
|
|
|
|
|
|
|
|
| ## BibTeX |
| ``` |
| @inproceedings{chen2024x360, |
| title={360+x: A Panoptic Multi-modal Scene Understanding Dataset}, |
| author={Chen, Hao and Hou, Yuqi and Qu, Chenyuan and Testini, Irene and Hong, Xiaohan and Jiao, Jianbo}, |
| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, |
| year={2024} |
| } |
| ``` |
