Text-to-Image Generation

83 papers with code • 9 benchmarks • 9 datasets

This task refers to image generation based on a given sentence or sequence of words.

Libraries

Use these libraries to find Text-to-Image Generation models and implementations
3 papers
1,799
3 papers
310
2 papers
1,235
See all 9 libraries.

Most implemented papers

Show and Tell: A Neural Image Caption Generator

karpathy/neuraltalk CVPR 2015

Experiments on several datasets show the accuracy of the model and the fluency of the language it learns solely from image descriptions.

Generative Adversarial Text to Image Synthesis

reedscot/icml2016 17 May 2016

Automatic synthesis of realistic images from text would be interesting and useful, but current AI systems are still far from this goal.

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

hanzhanggit/StackGAN ICCV 2017

Synthesizing high-quality images from text descriptions is a challenging problem in computer vision and has many practical applications.

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

taoxugit/AttnGAN CVPR 2018

In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation.

StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

hanzhanggit/StackGAN 19 Oct 2017

In this paper, we propose Stacked Generative Adversarial Networks (StackGAN) aiming at generating high-resolution photo-realistic images.

High-Resolution Image Synthesis with Latent Diffusion Models

compvis/latent-diffusion CVPR 2022

By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond.

Taming Transformers for High-Resolution Image Synthesis

CompVis/taming-transformers CVPR 2021

We demonstrate how combining the effectiveness of the inductive bias of CNNs with the expressivity of transformers enables them to model and thereby synthesize high-resolution images.

Zero-Shot Text-to-Image Generation

openai/DALL-E 24 Feb 2021

Text-to-image generation has traditionally focused on finding better modeling assumptions for training on a fixed dataset.

DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis

MinfengZhu/DM-GAN CVPR 2019

If the initial image is not well initialized, the following processes can hardly refine the image to a satisfactory quality.

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction

Maluuba/GeNeVA ICCV 2019

Conditional text-to-image generation is an active area of research, with many possible applications.