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CRD-CGAN: Category-Consistent and Relativistic Constraints for Diverse Text-t...
Generating photo-realistic images from a text description is a challenging problem in computer vision. Previ- ous works have shown promising performance to generate synthetic... -
CSI2Image: Image Reconstruction from Channel State Information Using Generati...
This study proposes CSI2Image, a novel channel-state-information (CSI)-to-image conversion method based on generative adversarial networks (GANs). -
Pneumoniamnist
Biomedical image analysis, data augmentation, Generative Adversarial Networks (GANs), synthetic images -
Toward a Visual Concept Vocabulary for GAN Latent Space
A new method for building open-ended vocabularies of primitive visual concepts represented in a GAN's latent space. -
Density Estimation Using Real NVP
This dataset has no description
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Alternating Back-Propagation for Generator Networks
This dataset has no description
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Wasserstein GAN
This dataset has no description
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Flexible Prior Distributions for Deep Generative Models
The dataset induced prior distribution is learned using a secondary GAN named PGAN. This prior is then used to further train the original GAN. -
Bach Chorales
The Bach Chorales dataset is used to evaluate the quality of fake samples generated with the Generative Adversarial Networks framework. -
RaSeedGAN: Randomly-SEEDed super-resolution GAN for sparse measurements
A novel deep-learning approach based on generative adversarial networks to perform super-resolution reconstruction of sparse measurements. -
Synthetic-Neuroscore: Using a neuro-AI interface for evaluating generative ad...
Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. However,... -
Neuro-AI Interface for Evaluating Generative Adversarial Networks
Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. However,... -
YuruGAN: Yuru-Chara Mascot Generator Using Generative Adversarial Networks Wi...
A yuru-chara is a mascot character created by local governments and companies for publicizing information on areas and products. Because it takes various costs to create a... -
Understanding GANs: the LQG Setting
The authors used a simple benchmark where the data has a high-dimensional Gaussian distribution. -
W-space of StyleGAN2
The dataset used in the paper is the W-space of StyleGAN2, which is a latent space of a generative adversarial network (GAN) model. -
Self-supervised and semi-supervised learning for GANs
Self-supervised and semi-supervised learning for GANs -
Semi-supervised conditional GANs
Semi-supervised conditional GANs
