Datasets:
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license: cc-by-nc-4.0
task_categories:
- video-generation
- computer-vision
language:
- en
pretty_name: MACE-Dance
size_categories:
- 10K<n<100K
---
# 🎵 MACE-Dance Dataset
**MACE-Dance** is a large-scale dataset for **music-driven dance video generation**, released with our SIGGRAPH 2026 paper:
> **MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation**
It is designed to support research on generating dance videos that are both:
- 🕺 **kinematically plausible**
- 🎨 **visually coherent**
- 🎼 **well aligned with music**
---
## ✨ Overview
The dataset contains approximately:
- **70K** dance video clips
- **5–10 seconds** per clip
- **116 hours** in total
- **20+ dance genres**
The data is curated from two complementary sources:
### 1. Motion-centric subset
- Derived from **FineDance**
- Front-view rendered dance videos from 3D motion sequences
- Focused on **professional dance motion quality**
### 2. Appearance-centric subset
- Collected from high-engagement internet dance videos
- Focused on **visual appearance diversity and realism**
This design helps benchmark both **motion quality** and **appearance quality** in music-driven dance video generation.
---
## 📂 Folder Structure
```bash
MACE-Dance/
├── Appearance/
└── Kinematic/
```
> The exact file organization may vary depending on the released version.
---
## 🧹 Data Curation
For the in-the-wild subset, we apply a multi-stage cleaning pipeline:
- ✂️ shot boundary detection
- 🚶 motion filtering
- 🧍 single-person filtering
- ⏱️ clip segmentation into 5–10 second windows
This improves data quality for the music-driven dance generation task.
---
## 🎯 Intended Usage
This dataset is intended for research on:
- **music-driven dance video generation**
- **music-driven 3D dance generation**
- **pose-driven / motion-driven human animation**
- **motion and appearance evaluation**
---
## ⚠️ Notes
- This dataset is released for **research purposes only**.
- Please ensure your use complies with the corresponding license and platform policies.
- Some samples may originate from internet videos and are curated for academic research.
---
## 📚 Citation
If you find this dataset useful, please cite:
```bibtex
@article{yang2026macedance,
title={MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation},
author={Yang, Kaixing and Zhu, Jiashu and Tang, Xulong and Peng, Ziqiao and Zhang, Xiangyue and Wang, Puwei and Wu, Jiahong and Chu, Xiangxiang and Liu, Hongyan and He, Jun},
journal={ACM Transactions on Graphics (SIGGRAPH 2026)},
year={2026}
}
```
--- |