LATENT-VARIABLE GENERATIVE MODEL WITH A NOISE CONTRASTIVE PRIOR
Abstract:
One embodiment of the present invention sets forth a technique for generating images (or other generative output). The technique includes determining one or more first values for a set of visual attributes included in a plurality of training images, wherein the set of visual attributes is encoded via a prior network. The technique also includes applying a reweighting factor to the first value(s) to generate one or more second values for the set of visual attributes, wherein the second value(s) represent the first value(s) shifted towards one or more third values for the set of visual attributes, wherein the one or more third values have been generated via an encoder network. The technique further includes performing one or more decoding operations on the second value(s) via a decoder network to generate a new image that is not included in the plurality of training images.
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