HandEdit: A Unified Benchmark for Egocentric Human-to-Robot Dexterous Hand Image Editing
Robotic manipulation with dexterous hands is a cornerstone of Embodied AI, yet its progress is stifled by the high cost of collecting embodiment-aware teleoperation data. While abundant egocentric videos of human hands offer a scalable alternative, the profound discrepancies in appearance, articulation, and camera viewpoints between human and robotic data raise significant challenges for co-training. Though existing general image-editing models demonstrate strong capabilities, they lack necessary embodiment-specific priors to fully bridge this gap. In this work, we present HandEdit, a unified large-scale embodiment-aware image-editing dataset and benchmark specifically designed to transfo...
| Authors | Zhenjie Yang, Xingyu Jiao, Guopeng Zhong et al. |
|---|---|
| Primary category | cs.RO |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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