Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems 2023
DOI: 10.1145/3544548.3581226
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GANravel: User-Driven Direction Disentanglement in Generative Adversarial Networks

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Cited by 4 publications
(2 citation statements)
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“…For instance, Matejka et al proposed DreamLens, an interactive system for exploring and visualizing large-scale generative design datasets [43]. The most related generative design work to us includes those using AI models to support user's design [11,17,31,37,38,64,73]. Evirgen et al proposed GANzilla, a tool that allows users to discover image manipulation directions in Generative Adversarial Networks (GANs) [16].…”
Section: Interactive Support For Generative Designmentioning
confidence: 99%
See 1 more Smart Citation
“…For instance, Matejka et al proposed DreamLens, an interactive system for exploring and visualizing large-scale generative design datasets [43]. The most related generative design work to us includes those using AI models to support user's design [11,17,31,37,38,64,73]. Evirgen et al proposed GANzilla, a tool that allows users to discover image manipulation directions in Generative Adversarial Networks (GANs) [16].…”
Section: Interactive Support For Generative Designmentioning
confidence: 99%
“…Evirgen et al proposed GANzilla, a tool that allows users to discover image manipulation directions in Generative Adversarial Networks (GANs) [16]. Its follow-up work, GANravel, focuses on disentangling editing directions in GANs [17]. To achieve this, both GANzilla and GANravel adjust the coefficients in GAN's latent space.…”
Section: Interactive Support For Generative Designmentioning
confidence: 99%