AI Image Generators List: 100+

Our comprehensive list of over 100 AI image generators includes everything from GANs and VAEs to style transfer and super-resolution. Find your images creation AI tool in this complete list, ordered alphabetically.

AI Image Generators

An artificial intelligence AI image generator is a specific kind of model that has been taught to create fresh images based on a series of input photographs. In order to create images that are somewhat similar to the input data but not quite identical, it uses methods from computer vision and deep learning.

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There are several types of technologies for AI image generation:

Generative Adversarial Network

A sort of neural network called a GAN (Generative Adversarial Network) is used to create new images by learning from a training dataset. The generator and discriminator networks in GANs collaborate to produce new images that are comparable to the training dataset.

Research organizations and businesses frequently create and use GANs for a variety of purposes, including picture production. The GANs business model could entail charging other businesses or organizations to utilize the technology, or it could involve making money by selling goods or services that incorporate GANs for AI image generation.

VAEs (Variational Autoencoders) 

Those are a class of neural network that are used to produce images by discovering a condensed form of the data. In VAEs, the input data is mapped to a latent space by an encoder network, and the latent space is mapped back to the output data by a decoder network.

Similar to GANs, VAEs are frequently created and employed by research organizations and businesses for a range of applications, including picture production. The business model for VAEs could involve charging other businesses or organizations to utilize the technology under license, or it could entail making money by selling goods or services that make use of VAEs to create AI images.

Neural Style Transfer

Neural Style Transfer is a method for transferring one picture’s style to another image using a convolutional neural network. It’s unclear how the Neural Style Transfer technique’s creators profit from it.


This is a form of GAN that was created specifically for producing high-quality images of faces and other objects. It is not clear how NVIDIA generates revenue from StyleGAN specifically, but the company generates revenue through the sale of graphics processing units (GPUs) and other products and services.

Autoregressive models

Models that predict individual pixels of an image one at a time using the context of previously generated pixels include the autoregressive models PixelRNN and PixelCNN.

Style transfer

This technique uses deep learning to transfer the style of one image to another.


Super-resolution is a technique that uses deep learning to enhance the resolution of an image by increasing the number of pixels.

Flow-based models

These models are similar to VAEs, but use normalizing flows to learn a transformation of the latent representation that makes it easy to sample new images.

Generative Pre-trained Transformer (GPT-2)

GPT-2 is a type of transformer-based model that can generate images based on text descriptions.


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AI Image Generators

The most complete list of image generators in the market.

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