ACE-Data-0: A Large-Scale Multimodal Dataset for Embodied AI
liuziwei7 · x · 2026-08-01
ACE-Data-0 is a newly released, large-scale synchronized multimodal dataset designed to turn real home environments into supervision for embodied AI models.
Key Highlights:
- Ambient Capture Engine (ACE): A capture system that transforms ordinary rooms into recording studios, observing household activity at both table-scale and room-scale.
- Unified Multimodal Alignment: The dataset includes ego- and exo-view videos, human and hand motion, object trajectories, audio, and tactile sensing. All signals are strictly aligned on a single timeline and a shared coordinate system.
- Solving Long-Horizon Needs: While existing datasets capture fragmented atomic actions, ACE-Data-0 focuses on long-horizon processes (e.g., making tea, wiping a counter) lasting minutes. It captures the full evolution of perception, locomotion, dexterous manipulation, contact, and sound.
Related event: ACE-Data-0: A New Multimodal Embodied AI Dataset(3 posts)→
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