humaidtech/EgoViz-120
7.25 TB
AI & ML interests
data, ai, robotics
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Leverage Physical Superintelligence, with real-world data.
humaid.co · LinkedIn · GitHub · info@humaid.co
We collect real-world egocentric demonstration data for robotics — across manufacturing, warehouse, hospitality and food-service environments. Trained operators wear calibrated multi-sensor rigs on real jobs, and we run the whole pipeline from capture through annotation, quality control and delivery.
Not lab data. Not scripted. People doing their actual work.
What we capture
| Egocentric | Stereo RGB-D, global shutter, 1920×1200 @ 30 fps |
| Wrists | Dual wrist cameras, synchronized |
| Depth | 16-bit, losslessly compressed |
| IMU | ~200 Hz, head and both wrists |
| Hands | 21-keypoint 3D model per hand |
| Labels | Temporal action segmentation + natural-language descriptions |
| Format | MCAP, every signal on a shared clock |
Open datasets
🎬 EgoViz-120
120 hours · 5,392 clips · 7.25 TB · CC-BY-4.0
Synchronized egocentric demonstrations of real cleaning, cooking and facility work. Stereo ego video, two wrist cameras, depth, three IMUs, 3D hand pose and frame-level action labels, in a single self-contained MCAP per clip.
Working with us
We build custom datasets against a spec: environments, tasks, sensor configuration, annotation schema and volume. 50+ companies served, 12+ countries, 55,000+ operators across our partner networks.
If you are training manipulation or humanoid policies and the bottleneck is real-world data, get in touch — info@humaid.co.
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