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Inferring object properties from human interaction and transferring them to new motions
2021
Computational Visual Media
AbstractHumans regularly interact with their surrounding objects. Such interactions often result in strongly correlated motions between humans and the interacting objects. We thus ask: "Is it possible to infer object properties from skeletal motion alone, even without seeing the interacting object itself?" In this paper, we present a fine-grained action recognition method that learns to infer such latent object properties from human interaction motion alone. This inference allows us to
doi:10.1007/s41095-021-0218-8
fatcat:3ign7zuhajgsjjavi3kjk6tqoq