187 citations · 575 across the 29 of their papers we have counts for
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Navigating the GAN Parameter Space for Semantic Image Editing
Anton Cherepkov, Andrey Voynov, Artem Babenko
Generative Adversarial Networks (GANs) are currently an indispensable tool for visual editing, being a standard component of image-to-image translation and image restoration pipeli…
Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
The recent rise of unsupervised and self-supervised learning has dramatically reduced the dependency on labeled data, providing effective image representations for transfer to down…
Editable Neural Networks
Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitriy Pyrkin +2
These days deep neural networks are ubiquitously used in a wide range of tasks, from image classification and machine translation to face identification and self-driving cars. In m…
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
Andrey Voynov, Artem Babenko
The latent spaces of GAN models often have semantically meaningful directions. Moving in these directions corresponds to human-interpretable image transformations, such as zooming…