AI RESEARCH
HumanNet: Scaling Human-centric Video Learning to One Million Hours
arXiv CS.CV
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ArXi:2605.06747v1 Announce Type: new Progress in embodied intelligence increasingly depends on scalable data infrastructure. While vision and language have scaled with internet corpora, learning physical interaction remains constrained by the lack of large, diverse, and richly annotated human activity data. We present HumanNet, a one-million-hour human-centric video corpus that captures how humans interact with the physical world at scale.