DexYCB
NVIDIA RGB-D benchmark: 582K frames of 10 humans grasping 20 YCB objects, captured from 8 RealSense cameras with hand/object pose labels.
| Year | 2021 |
|---|---|
| Episodes | 1,000 |
| Total hours | 1 |
| Embodiments | human |
| Modalities | depth, segmentation, rgb |
| Task categories | manipulation |
| License | CC-BY-NC-4.0 |
| Access | open |
| Maintainer | NVIDIA (with University of Washington) |
DexYCB is a large-scale RGB-D dataset of 582,000 frames capturing 10 human subjects grasping 20 objects from the YCB-Video set, recorded synchronously from 8 calibrated Intel RealSense D415 cameras around a tabletop (640x480 @ 30fps, 1,000 trials total). Each frame is annotated with segmentation masks, 6D object poses, MANO hand pose, and 2D/3D hand joints. It supports tasks including 2D detection, 6D object pose estimation, 3D hand pose estimation, and a robotics-relevant safe human-to-robot handover grasp-generation task.