Datasets:
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README.md
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<!-- Provide a quick summary of the dataset. -->
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## Dataset Details
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<!-- Provide a longer summary of what this dataset is. -->
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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### Dataset Sources [optional]
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- **Repository:**
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- **Paper
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- **Demo
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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[More Information Needed]
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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<!-- Provide a quick summary of the dataset. -->
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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).
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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.
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## Dataset Details
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- **Curated by:** [Rosie Lab](www.rosielab.ca), Simon Fraser University
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- **Language(s):** English
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- **License:** CC-BY-NC-4.0, except for audio in .mp4 files where rights retained by owners
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### Dataset Sources [optional]
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- **Repository:** https://github.com/rosielab/compas3d
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- **Paper:** Coming soon!
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- **Demo:** Coming soon!
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## 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:
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- Solo Motion Segmentation, Classification, Transcription (Automatic Speech Recognition)
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- Solo Motion Generation (Speech Synthesis)
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- Follower Motion Generation (Listener Speech Synthesis)
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- Pair Motion Generation and Analysis (Conversation Synthesis)
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- Style Transfer (Proficiency Adaptation)
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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