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Author (up) Diego Porres edit   pdf
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  Title Discriminator Synthesis: On reusing the other half of Generative Adversarial Networks Type Conference Article
  Year 2021 Publication Machine Learning for Creativity and Design, Neurips Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Generative Adversarial Networks have long since revolutionized the world of computer vision and, tied to it, the world of art. Arduous efforts have gone into fully utilizing and stabilizing training so that outputs of the Generator network have the highest possible fidelity, but little has gone into using the Discriminator after training is complete. In this work, we propose to use the latter and show a way to use the features it has learned from the training dataset to both alter an image and generate one from scratch. We name this method Discriminator Dreaming, and the full code can be found at this https URL.  
  Address Virtual; December 2021  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference NEURIPSW  
  Notes ADAS; 601.365 Approved no  
  Call Number Admin @ si @ Por2021 Serial 3597  
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