Stylistic and Spatial Disentanglement in GANs
This dissertation tackles the problem of entanglement in Generative Adversarial Networks (GANs). The key insight is that disentanglement in GANs can be improved by differentiating between the content, and the operations performed on that content. For example, the identity of a generated face can be...
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| Language: | en |
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2021
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| Online Access: | http://hdl.handle.net/10754/670641 |