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Found 2 papers, 1 papers with code
SC2GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space
We propose a novel framework SC$^2$GAN that achieves disentanglement by re-projecting low-density latent code samples in the original latent space and correcting the editing directions based on both the high-density and low-density regions.
Exploring Gradient-based Multi-directional Controls in GANs
Generative Adversarial Networks (GANs) have been widely applied in modeling diverse image distributions.
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