UGC360 / README.md
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---
license: cc-by-4.0
tags:
- 360-degree
- video compression
- spherical video
- image sequence
- video
- pytorch-compatible
pretty_name: UGC360
size_categories:
- 10K<n<100K
configs:
- config_name: UGC360-S
- config_name: UGC360-M
- config_name: UGC360-L
---
# UGC360
![Preview](./preview.jpg)
Dataset of 6866 9-frame 360-degree video sequences collected from 1321 unique videos from Vimeo and Youtube licensed under a Creative Commons License.
The dataset is split into three subsets UGC360-S, UGC360-M, and UGC360-L to ease data handling.
| Subset | Resolutions | Minimum | Maximum | Clips |
|----------|:-----------:|:---------:|:---------:|------:|
| [UGC360-S Part 1](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-S.z01?download=true), [UGC360-S Part 2](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-S.z02?download=true), [UGC360-S Part 3](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-S.z03?download=true), [UGC360-S Part 4](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-S.zip?download=true) | .5K - 2.5K | 640x320 | 2560x1440 | 5080 |
| [UGC360-M Part 1](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-M.z01?download=true), [UGC360-M Part 2](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-M.z02?download=true), [UGC360-M Part 3](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-M.zip?download=true) | 3K - 6K | 3072x1536 | 5760x2880 | 1618 |
| [UGC360-L](https://huggingface.co/datasets/FAU-LMS/UGC360/resolve/main/UGC360-L.zip?download=true) | 8K | 7680x3840 | 7680x4320 | 168 |
## Unpacking the dataset
Due to file size limitations on the Hugging Face platform, we had to upload the UGC360-S and UGC360-M subset archives as multipart zip files.
To unzip these multipart zips, download all multipart zip files (.z01, z02, ..., .zip) of a subset to the same folder.
From that folder, execute
```shell
zip -s- UGC360-S.zip -O UGC360-S-all.zip
unzip UGC360-S-all.zip
```
Replace 'UGC360-S' by 'UGC360-M' to do the same for the UGC360-M subset. The directory structure of the final dataset should then follow
```txt
.
β”œβ”€β”€ UGC360-L
β”‚ β”œβ”€β”€ ugc360-l.csv
β”‚ β”œβ”€β”€ <video_id>/
β”‚ β”‚ β”œβ”€β”€ <clip_id>/
β”‚ β”‚ β”‚ β”œβ”€β”€ 01.png
β”‚ β”‚ β”‚ β”œβ”€β”€ 02.png
β”‚ β”‚ β”‚ β”œβ”€β”€ 03.png
β”‚ β”‚ β”‚ β”œβ”€β”€ ...
β”‚ β”‚ β”‚ └── 09.png
β”‚
β”œβ”€β”€ UGC360-M
β”‚ β”œβ”€β”€ ugc360-m.csv
β”‚ β”œβ”€β”€ <video_id>/
β”‚ β”‚ β”œβ”€β”€ <clip_id>/
β”‚ β”‚ β”‚ β”œβ”€β”€ 01.png
β”‚ β”‚ β”‚ └── ...
β”‚
└── UGC360-S
β”œβ”€β”€ ugc360-s.csv
β”œβ”€β”€ <video_id>/
β”‚ β”œβ”€β”€ <clip_id>/
β”‚ β”‚ β”œβ”€β”€ 01.png
β”‚ β”‚ └── ...
```
## License
The **UGC360 subset** is licensed under **Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)**.
Each individual clip within the dataset originates from videos published under various **Creative Commons licenses** (e.g., CC-BY, CC-BY-SA). The corresponding license for each clip is documented in the CSV metadata files within each subset folder:
- `UGC360-S/ugc360-s.csv`
- `UGC360-M/ugc360-m.csv`
- `UGC360-L/ugc360-l.csv`
Each row contains a `license` column indicating the license of the source video.
### Attribution and Compliance
We collected only videos explicitly marked as Creative Commons on their original platforms (YouTube or Vimeo). For each clip, the dataset includes attribution information:
- Video ID
- Clip ID
- Publisher
- Original video URL
- License type
- Publication date
If you use this dataset, you are required to:
1. Comply with the CC license of each video
2. Attribute the dataset as a whole as:
> UGC360 Dataset (CC BY-SA 4.0)
If you redistribute or modify this dataset, you must do so under the same license (CC BY-SA 4.0).
## Publication
If you use this dataset, please cite
```
@inproceedings{regensky2025nvc360,
title = {Beyond Perspective: Neural 360-Degree Video Compression},
author = {Andy Regensky and Marc Windsheimer and Fabian Brand and AndrΓ© Kaup},
booktitle = {accepted for the IEEE/CVF International Conference on Computer Vision (ICCV)},
year = {2025}
}
```