Producing Higher-Quality Samples Of Natural Images

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• access a plurality of generative adversarial networks (GANs) that are each applied to a particular level k of a Laplacian pyramid, wherein each GAN comprises a generative model Gk and a discriminative model Dk, wherein, at each level k:
• the generative model Gk takes as input a noise vector zk and outputs a generated image {tilde over (h)}k;
• and
• the discriminative model Dk takes as input either the generated image {tilde over (h)}k or a real image hk drawn from a set of training data, and outputs a probability that the input was the real image hk;
• generate a sample image Ĩk from the generated images {tilde over (h)}k, wherein the sample image is based at least in part on the probabilities outputted by each of the discriminative models Dk at each level k of the Laplacian pyramid and the generated images {tilde over (h)}k;
• and
• provide the sample image Ĩk for display on a display screen of a client device of a user of a communications network.

A system comprising:

• one or more processors;
• and
• one or more computer-readable non-transitory storage media coupled to one or more of the processors and comprising instructions operable when executed by one or more of the processors to cause the system to:
• access a plurality of generative adversarial networks (GANs) that are each applied to a particular level k of a Laplacian pyramid, wherein each GAN comprises a generative model Gk and a discriminative model Dk, wherein, at each level k:
• the generative model Gk takes as input a noise vector zk and outputs a generated image {tilde over (h)}k;
• and
• the discriminative model Dk takes as input either the generated image {tilde over (h)}k or a real image hk drawn from a set of training data, and outputs a probability that the input was the real image hk;
• generate a sample image Ĩk from the generated images {tilde over (h)}k, wherein the sample image is based at least in part on the probabilities outputted by each of the discriminative models Dk at each level k of the Laplacian pyramid and the generated images {tilde over (h)}k;
• and
• provide the sample image Ĩk for display on a display screen of a client device of a user of a communications network.