Text-to-Image Generation

34 papers with code • 8 benchmarks • 5 datasets

Libraries

Use these libraries to find Text-to-Image Generation models and implementations

Most implemented papers

MirrorGAN: Learning Text-to-image Generation by Redescription

komiya-m/MirrorGAN CVPR 2019

Generating an image from a given text description has two goals: visual realism and semantic consistency.

Controllable Text-to-Image Generation

mrlibw/ControlGAN NeurIPS 2019

In this paper, we propose a novel controllable text-to-image generative adversarial network (ControlGAN), which can effectively synthesise high-quality images and also control parts of the image generation according to natural language descriptions.

Semantic Object Accuracy for Generative Text-to-Image Synthesis

tohinz/semantic-object-accuracy-for-generative-text-to-image-synthesis 29 Oct 2019

To address these challenges we introduce a new model that explicitly models individual objects within an image and a new evaluation metric called Semantic Object Accuracy (SOA) that specifically evaluates images given an image caption.

TediGAN: Text-Guided Diverse Face Image Generation and Manipulation

weihaox/TediGAN CVPR 2021

In this work, we propose TediGAN, a novel framework for multi-modal image generation and manipulation with textual descriptions.

Towards Open-World Text-Guided Face Image Generation and Manipulation

weihaox/TediGAN 18 Apr 2021

To be specific, we propose a brand new paradigm of text-guided image generation and manipulation based on the superior characteristics of a pretrained GAN model.

Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation

wcshin-git/te-vqgan 1 Dec 2021

Recently, vector-quantized image modeling has demonstrated impressive performance on generation tasks such as text-to-image generation.

MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis

HYOJINPARK/MC_GAN 3 May 2018

This block enables MC-GAN to generate a realistic object image with the desired background by controlling the amount of the background information from the given base image using the foreground information from the text attributes.

0.52 V-mm ITO-based Mach-Zehnder Modulator in Silicon Photonics

TruongTam/jsc 16 Aug 2018

Electro-optic modulators transform electronic signals into the optical domain and are critical components in modern telecommunication networks, RF photonics, and emerging applications in quantum photonics and beam steering.

Generating Multiple Objects at Spatially Distinct Locations

tohinz/multiple-objects-gan ICLR 2019

Our experiments show that through the use of the object pathway we can control object locations within images and can model complex scenes with multiple objects at various locations.

Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge

qiaott/LeicaGAN NeurIPS 2019

Given a text description, we immediately imagine an overall visual impression using this prior and, based on this, we draw a picture by progressively adding more and more details.