Synthesizing Programs for Images usingReinforced Adversarial Learning

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Synthesizing Programs for Images usingReinforced Adversarial Learning: Summary of the ICML 2018 paper http://proceedings.mlr.press/v80/ganin18a.html

Presented by

1. Nekoei, Hadi [Quest ID: 20727088]

Motivation

Conventional neural generative models have major problems.

  • Firstly, it is not clear how to inject knowledge to the model about the data.
  • Secondly, latent space is not easily interpretable.

The provided solution in this paper is to generate programs to incorporate tools, e.g. graphics editors, illustration software, CAD. and creating more meaningful API(sequence of complex actions vs raw pixels).

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