31 citations · 68 across the 5 of their papers we have counts for
5 papers
Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously
Kyungjune Baek, Duhyeon Bang, Hyunjung Shim
We propose a novel framework for simultaneously generating and manipulating the face images with desired attributes. While the state-of-the-art attribute editing technique has achi…
Resembled Generative Adversarial Networks: Two Domains with Similar Attributes
Duhyeon Bang, Hyunjung Shim
We propose a novel algorithm, namely Resembled Generative Adversarial Networks (GAN), that generates two different domain data simultaneously where they resemble each other. Althou…
Discriminator Feature-based Inference by Recycling the Discriminator of GANs
Duhyeon Bang, Seoungyoon Kang, Hyunjung Shim
Generative adversarial networks (GANs)successfully generate high quality data by learning amapping from a latent vector to the data. Various studies assert that the latent space of…
MGGAN: Solving Mode Collapse using Manifold Guided Training
Duhyeon Bang, Hyunjung Shim
Mode collapse is a critical problem in training generative adversarial networks. To alleviate mode collapse, several recent studies introduce new objective functions, network archi…
Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang, Hyunjung Shim
Despite the success of generative adversarial networks (GANs) for image generation, the trade-off between visual quality and image diversity remains a significant issue. This paper…