17 мая 2016 г. · In this work, we develop a novel deep architecture and GAN formulation to effectively bridge these advances in text and image model- ing, ...

In this work, we develop a novel deep architecture and GAN formulation to effectively bridge these advances in text and image modeling, translating visual ...

This is the code for our ICML 2016 paper on text-to-image synthesis using conditional GANs. You can use it to train and sample from text-to-image models.

In this work, we develop a novel deep architecture and GAN formulation to effectively bridge these advances in text and image modeling, translating visual ...

5 июн. 2016 г. · Our main contribution in this work is to develop a sim- ple and effective GAN architecture and training strat- egy that enables compelling text ...

21 мая 2016 г. · In this work, we develop a novel deep architecture and GAN formulation to effectively bridge these advances in text and image modeling, ...

We critically examine current strategies to evaluate text-to-image synthesis models, highlight shortcomings, and identify new areas of research.

1 авг. 2023 г. · Generative adversarial text to image synthesis proposes matching-aware discriminator (GAN-CLS), learning with manifold interpolation (GAN-INT), & combined one ...

This paper aims to extend state of the art for GAN-based text-to-image synthesis by improving perceptual quality of generated images by optimizing on ...

There are, however, some text to image synthesis algorithms that use GAN (Generative Adversarial Network) that attempt to directly map words and characters to ...