Closed-Form Factorization of Latent Semantics in GANs

13 Jul 2020 Yujun Shen Bolei Zhou

A rich set of interpretable dimensions has been shown to emerge in the latent space of the Generative Adversarial Networks (GANs) trained for synthesizing images. In order to identify such latent dimensions for image editing, previous methods typically annotate a collection of synthesized samples and train linear classifiers in the latent space... (read more)

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