Update README.md

README.md

@@ -1,71 +1,71 @@
----
-license: cc-by-nc-sa-4.0
----
-
-# <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.
-
-## About This Repo
-
-This repository stores the pretrained models of the 360+x dataset. For more code information, please check our [official
-code repository](https://github.com/chqwer2/360x_Video_Experiments).
-
-## 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, totaling 28 scene categories.
-- **Short Clips:** The videos have been segmented into 1,380 shorter clips, each approximately 10 seconds long, totaling
-  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 (640x320 for panoramic and binocular
-videos, 569x320 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}
-}
+---
+license: cc-by-nc-sa-4.0
+---
+
+# <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.
+
+## About This Repo
+
+This repository stores the pretrained models of the 360+x dataset. For more code information, please check our [official
+code repository](https://github.com/x360dataset/x360dataset-kit).
+
+## 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, totaling 28 scene categories.
+- **Short Clips:** The videos have been segmented into 1,380 shorter clips, each approximately 10 seconds long, totaling
+  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 (640x320 for panoramic and binocular
+videos, 569x320 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}
+}
 ```