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README.md
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---
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license: cc-by-nc-sa-4.0
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---
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# <i>360+x</i> Dataset
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For more information, please feel free to check our [project page](https://x360dataset.github.io/).
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## Overview
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360+x dataset introduces a unique panoptic perspective to scene understanding, differentiating itself from traditional
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datasets by offering multiple viewpoints and modalities, captured from a variety of scenes
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### Key Features:
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- **Multi-viewpoint Captures:** Includes 360° panoramic video, third-person front view video, egocentric monocular
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video, and egocentric binocular video.
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- **Rich Audio Modalities:** Features normal audio and directional binaural delay.
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- **2,152 multi-model videos** captured by 360 cameras and Spectacles camera (8579k frames in total) Captured in 17
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cities across 5 countries, covering 28 scenes ranging from Artistic Spaces to Natural Landscapes.
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- **Action Temporal Segmentation:** Provides labels for 38 action instances for each video pair.
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## About This Repo
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This repository stores the pretrained models of the 360+x dataset. For more code information, please check our [official
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code repository](https://github.com/chqwer2/360x_Video_Experiments).
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## Dataset Details
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### Project Description
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- **Developed by:** Hao Chen, Yuqi Hou, Chenyuan Qu, Irene Testini, Xiaohan Hong, Jianbo Jiao
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- **Funded by:** the Ramsay Research Fund, and the Royal Society Short Industry Fellowship
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- **License:** Creative Commons Attribution-NonCommercial-ShareAlike 4.0
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### Sources
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- **Repository:** Coming Soon
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- **Paper:** https://arxiv.org/abs/2404.00989
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## Dataset Statistics
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- **Total Videos:** 2,152, split between 464 videos captured using 360 cameras and 1,688 with Spectacles cameras.
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- **Scenes:** 15 indoor and 13 outdoor, totaling 28 scene categories.
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- **Short Clips:** The videos have been segmented into 1,380 shorter clips, each approximately 10 seconds long, totaling
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around 67.78 hours.
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- **Frames:** 8,579k frames across all clips.
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## Dataset Structure
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Our dataset offers a comprehensive collection of panoramic videos, binocular videos, and third-person videos, each pair
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of videos accompanied by annotations. Additionally, it includes features extracted using I3D, VGGish, and ResNet-18.
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Given the high-resolution nature of our dataset (5760x2880 for panoramic and binocular videos, 1920x1080 for
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third-person front view videos), the overall size is considerably large. To accommodate diverse research needs and
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computational resources, we also provide a lower-resolution version of the dataset (640x320 for panoramic and binocular
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videos, 569x320 for third-person front view videos) available for download.
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<b>In this repo, we provide the lower-resolution version of the dataset. To access the high-resolution version, please
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visit the <a href="https://x360dataset.github.io/">official website</a>.</b>
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## BibTeX
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```
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@inproceedings{chen2024x360,
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title={360+x: A Panoptic Multi-modal Scene Understanding Dataset},
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author={Chen, Hao and Hou, Yuqi and Qu, Chenyuan and Testini, Irene and Hong, Xiaohan and Jiao, Jianbo},
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booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
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year={2024}
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}
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```
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