3 papers
cs.RO2026
OmniDex: Scaling Dexterous Hand Grasping to Diverse Cluttered Scenes
Naiyu Fang, Zhongjin Luo, Yuxin Mo +7
Dexterous grasping is the foundational primitive in embodied AI, demanding massive data to train robust models. As real-world data collection is expensive, simulation has become th…
cs.CV2026
ACE-Ego-Hand: Repurposing Video Diffusion Models for Occlusion-Robust Egocentric 3D Hand Motion Recovery
Yufei Liu, Xixi Wang, Hao Li +8
Egocentric video offers scalable manipulation data for embodied AI, yet recovering metric 3D hand trajectories remains challenging due to severe object occlusion and frequent out-o…
cs.CV2026
The Surprising Effectiveness of Video Diffusion Models for Hand Motion Reconstruction
Yuxi Wang, Chengkai Jin, Yufei Liu +6
4D hand motion reconstruction from egocentric video is bottlenecked by clear limitations of existing methods: image-based pipelines depend on a detector that fails under heavy occl…