---
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}
}
```

---