2024/07/03 · Text-to-image generation models generate photo-realistic images from textual descriptions, typically using GANs and BiLSTM networks.

2024/07/05 · Then, a text-edited image is generated by combining the style feature from the original image and the content feature from the target text.

An Improved AttnGAN Model for Text-to-Image Synthesis. https://doi.org/10.1007/978-3-031-58535-7_12. Journal: Communications in Computer and Information ...

This is the official Pytorch implementation of the paper Improving Text-to-Image Synthesis Using Contrastive Learning

In this paper, we investigate the use of different Transformer models such as BERT, GPT2, XLNet with AttnGAN to solve the challenge of extracting semantic ...

Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial ...

2021/07/06 · We evaluate our approach over two popular text-to-image synthesis models, AttnGAN and DM-GAN, on datasets CUB and COCO, respectively.

In this paper, we propose an Attentional Generative Ad- versarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained ...

8.03. Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion ... 13.86. Vector Quantized Diffusion Model for Text-to-Image Synthesis.

A Realistic Image Generation of Face From Text Description Using the Fully Trained Generative Adversarial Networks · DF-GAN: Deep Fusion Generative Adversarial ...