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Learning disentangled invariant representations for one-shot instance recognition

  • US 10,445,622 B2
  • Filed: 09/15/2017
  • Issued: 10/15/2019
  • Est. Priority Date: 05/18/2017
  • Status: Active Grant
First Claim
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1. A method of one-shot joint instance and pose recognition in an artificial neural network, comprising:

  • training a generator for generating an orbit, the generator trained using a two-branch encoder-decoder architecture that receives two images of two different objects in a same pose;

    receiving a first instance of a reference object from a reference image, the reference object having a first identity and a first pose in the first instance;

    generating, via the trained generator, a first orbit of the reference object comprising a plurality of additional poses including a second pose for the reference object; and

    recognizing a second instance of an example object from an example image, the example object having the first identity and the second pose in the second instance.

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