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Interactive object understanding, or what we can do to objects and how is along-standing goal of computer vision. In this paper, we tackle this problemthrough observation of human hands in in-the-wild egocentric videos. Wedemonstrate that observation of what human hands interact with and how canprovide both the relevant data and the necessary supervision. Attending tohands, readily localizes and stabilizes active objects for learning and revealsplaces where interactions with objects occur. Analyzing the hands shows what wecan do to objects and how. We apply these basic principles on the EPIC-KITCHENSdataset, and successfully learn state-sensitive features, and objectaffordances (regions of interaction and afforded grasps), purely by observinghands in egocentric videos.

Human Hands as Probes for Interactive Object Understanding