Home | << 1 >> |
![]() |
Record | |||||
---|---|---|---|---|---|
Author | Diego Porres | ||||
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 | ||||
Publisher | Place of Publication | Editor | |||
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 | ||
Permanent link to this record |