# dataset

**Repository Path**: cui_duo/dataset

## Basic Information

- **Project Name**: dataset
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-07-17
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Dataset

## Introduction

This dataset is build to create relationship between dance motion and the music, which contains four types of dance, Cha-cha, Tango, Rumba and Waltz. 

In each directory, `audio.mp3` gives the audio files of the dance. `skeletons.json` describes the skeleton points of the dance, the `config.json` gives the start frames and the end frames (The dance sequence match part of the songs). The FPS of the dataset is 25 frames per second.


## Paper

This dataset is build along with the ACM-Multimedia regular paper & demo paper:

```
@inproceedings{tang2018dance,
	title={Dance with Melody: An LSTM-autoencoder Approach to Music-oriented Dance Synthesis},
	author={Tang, Taoran and Jia, Jia and Mao, Hanyang},
	booktitle={2018 ACM Multimedia Conference on Multimedia Conference},
	pages={1598--1606},
	year={2018},
	organization={ACM}
}
```

```
@inproceedings{tang2018anidance,
	title={AniDance: Real-Time Dance Motion Synthesize to the Song},
	author={Tang, Taoran and Mao, Hanyang and Jia, Jia},
	booktitle={2018 ACM Multimedia Conference on Multimedia Conference},
	pages={1237--1239},
	year={2018},
	organization={ACM}
}
```

## Notes

Let me know if something is wrong with the dataset.

Issues posted in this repository will not be noticed. If you have any question, please email [me](maohanyang789@163.com), or create an issue in [https://github.com/mhy12345/Music-to-Dance-Motion-Synthesis](https://github.com/mhy12345/Music-to-Dance-Motion-Synthesis).