AI RESEARCH
LOME: Learning Human-Object Manipulation with Action-Conditioned Egocentric World Model
arXiv CS.CV
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ArXi:2603.27449v1 Announce Type: new Learning human-object manipulation presents significant challenges due to its fine-grained and contact-rich nature of the motions involved. Traditional physics-based animation requires extensive modeling and manual setup, and importantly, it neither generalizes well across diverse object morphologies nor scales effectively to real-world environment. To address these limitations, we