| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - music |
| | - AIGC |
| | - art |
| | language: |
| | - en |
| | size_categories: |
| |
|
| | - 10K<n<100K |
| | --- |
| | # Dataset Card for LORIS |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** [LORIS](https://justinyuu.github.io/LORIS) |
| | - **Repository:** [OpenGVLab-LORIS](https://github.com/OpenGVLab/LORIS) |
| | - **Paper:** [2305.01319](https://arxiv.org/pdf/2305.01319.pdf) |
| | - **Point of Contact:** [yujiashuo](mailto:yujiashuo@pjlab.org.cn) |
| |
|
| | ### Dataset Summary |
| |
|
| | LORIS dataset is a large-scale rhythmic video soundtrack dataset that includes 86.43h long-term, high-quality raw videos with corresponding 2D poses, RGB features, and ameliorated audio waveforms. This dataset is originally used for the video background music generation task (a.k.a. video soundtracks). |
| |
|
| | ### Get Started |
| |
|
| | from datasets import load_dataset |
| | dataset = load_dataset("awojustin/LORIS") |
| | |
| |
|
| | ### Citation Information |
| |
|
| | @inproceedings{Yu2023Long, |
| | title={Long-Term Rhythmic Video Soundtracker}, |
| | author={Yu, Jiashuo and Wang, Yaohui and Chen, Xinyuan and Sun, Xiao and Qiao, Yu }, |
| | booktitle={International Conference on Machine Learning (ICML)}, |
| | year={2023} |
| | } |
| | |
