---
license: cc-by-nc-4.0
task_categories:
- text-to-video
language:
- en
tags:
- animation
- dance
- salsa
- interaction
- humanoid
- mocap
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset Name

<!-- Provide a quick summary of the dataset. -->

CoMPAS3D (Complex Multi-Level Person-Interaction Annotated Salsa Dataset) is a large-scale motion capture dataset designed to support research on nonverbal, physical communication through dance. It contains over 3 hours of improvised salsa duet performances by 18 dancers across beginner, intermediate, and professional skill levels. Each sequence features high-fidelity 3D motion data in the form of SMPL-X (.npz) files, along with video visualizations and synchronized audio (.mp4). We provide detailed frame-level annotations of move types, stylistic variation, and execution errors for 50% of the sequences (.txt).

Collected in a controlled studio using a 20-camera Vicon system at 120fps, the dataset includes 72 long-form sequences (each 2.5 minutes) of naturalistic leader-follower interaction. Participants were drawn from diverse dance backgrounds, and all provided informed consent for data release. CoMPAS3D offers a rich testbed for studying embodied dialogue, social fluency, and multi-agent coordination in AI and robotics.

## Dataset Details

### Dataset Description

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- **Curated by:** [Rosie Lab](www.rosielab.ca), Simon Fraser University
- **Language(s):** English
- **License:** CC-BY-NC-4.0, except for audio in .mp4 files where rights retained by owners

### Dataset Sources [optional]

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- **Repository:** https://github.com/rosielab/compas3d
- **Paper:** Coming soon!
- **Demo:** Coming soon!

## Uses

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This dataset was created to encourage research in socially interactive embodied AI and creative, expressive humanoid motion generation. As salsa contains a move vocabulary and implict grammar rules, we propose tasks that mirror those in spoken language processing:

- Solo Motion Segmentation, Classification, Transcription (Automatic Speech Recognition)
- Solo Motion Generation (Speech Synthesis)
- Follower Motion Generation (Listener Speech Synthesis)
- Pair Motion Generation and Analysis (Conversation Synthesis)
- Style Transfer (Proficiency Adaptation)

### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

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## Dataset Creation

### Curation Rationale

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### Source Data

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#### Data Collection and Processing

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#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

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## Bias, Risks, and Limitations

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### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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