Learning Image Representations Tied to Egomotion from Unlabeled Video

Abstract

Understanding how images of objects and scenes behave in response to specific egomotions is a crucial aspect of proper visual development, yet existing visual learning methods are conspicuously disconnected from the physical source of their images. We propose a new “embodied” visual learning paradigm, exploiting proprioceptive motor signals to train visual… (More)
DOI: 10.1007/s11263-017-1001-2

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