HandsOnWorld: Unconstrained Egocentric Video Generation with Camera-Disentangled Hand Control
We present HandsOnWorld, a framework for hand-controlled egocentric video generation that learns directly from unconstrained monocular video. Prior generators depend on 3D hand annotations from multi-view or marker-based motion capture, confining them to narrow, instrumented scene distributions. To bridge this gap, we introduce a protagonist-centered annotation pipeline that filters monocular 3D reconstructions at the action-semantic, image-quality, and 3D-geometric levels, yielding EgoVid-Pro, a dataset of clean, protagonist-only hand trajectories spanning 103K clips and roughly 12M frames across diverse everyday scenes. These unconstrained scenes exhibit substantial camera ego-motion th...
| Authors | Yushuo Chen, Xiaoyu Shi, Xiaoshi Wu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 2 July 2026 |
| Last updated at source | 14 August 2026 |
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