Video2Sim2Real turns a single human video into a deployable robot manipulation skill by reconstructing a digital twin, anchoring motions to object-centric simulator configurations, and bridging sim-to-real gaps with imitation learning and residual RL.
DexImit: Learning bimanual dexterous manipulation from monocular human videos.arXiv preprint arXiv:2602.10105, 2026
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SynManDex generates human-like dexterous grasps for robots from synthetic human pre-grasps via retargeting and force-closure optimization, reporting 86.4% stability, 4.67/5 human-likeness, 80.7% sim success, and 83.3% real-robot success.
citing papers explorer
-
Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video
Video2Sim2Real turns a single human video into a deployable robot manipulation skill by reconstructing a digital twin, anchoring motions to object-centric simulator configurations, and bridging sim-to-real gaps with imitation learning and residual RL.
-
SynManDex: Synthesizing Human-like Dexterous Grasps from Synthetic Human Pre-Grasps
SynManDex generates human-like dexterous grasps for robots from synthetic human pre-grasps via retargeting and force-closure optimization, reporting 86.4% stability, 4.67/5 human-likeness, 80.7% sim success, and 83.3% real-robot success.