3D Hand Pose Data for Dexterous Manipulation
Hand–object interaction data with 3D hand joints, contact points and object pose for dexterous manipulation and grasp planning. Request a hand-object sample from Shaip.
Dataset Specifications
| Target Buyer Teams | Dexterity Research Lead; Manipulation Team; Robot Hand Product Lead; VLA Data Lead |
| Representative Tasks | Grasp, rotate, insert, pour, fold, open, close, fasten, hand over and use tools |
| Capture / Modalities | Egocentric/exocentric RGB-D; optional gloves, hand trackers and tactile signals |
| Annotations / Metadata | 2D/3D hand joints, object masks and pose, contact points, grasp type, action phase and object state |
| Delivery Formats | MP4/RGB-D + JSON + point clouds + calibration where available |
| Scale (Illustrative)* | 500,000–5M annotated frames |
| Participants / Operators | 250–1,000 participants |
| Tasks / Scenarios | 20–100 manipulation tasks |
| Objects / Sites / Views | 100–500 objects |
| Recommended Engagement Scope | 100,000–300,000 frames across 15–30 objects and 8–15 tasks |
Builds on Shaip's egocentric capture, full-body keypoint and object-annotation capabilities.
View the related case study →Where This Dataset Is Used
This hand object interaction dataset is built for teams training dexterous manipulation, grasp planning and hand tracking models. Robotics companies, AR/VR teams and embodied AI labs use it as a 3D hand pose dataset for grasp synthesis, contact prediction, dexterous hand control and hand-object reconstruction. If you’re sourcing a hand tracking dataset, grasping dataset or object manipulation dataset with 3D hand joints, contact points and object pose, this dexterous manipulation data supports everything from dexterous robot hands to gesture-driven XR interfaces.
Request a Sample of the Hand–Object Interaction and Hand Pose Dataset
Tell us about the robot product or Physical AI system you’re building and we’ll respond with sample access, specifications and a proposal matched to your task.
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