Artificial Intelligence (AI) has made tremendous progress in the field of image generation in recent years. With the help of deep learning algorithms and advanced computational power, AI models can now generate highly realistic images that are indistinguishable from images captured by a camera.
One of the most popular AI image generation models is Generative Adversarial Networks (GANs). GANs consist of two neural networks, a generator and a discriminator, working against each other to generate and evaluate the images respectively. The generator produces the images, while the discriminator determines whether the generated images are realistic enough. This process continues until the generator is able to produce highly realistic images that fool the discriminator.
Another popular AI image generation technique is Style Transfer, which allows the user to transfer the style of one image onto another image while preserving its content. This technique can be used to create unique and interesting images by combining the styles of multiple images. Below is an example of transferring the style of an image of real human into android:
AI image generation can have many practical applications, such as generating new and diverse training data for computer vision models, creating images for video games and movies, and even creating realistic product images for e-commerce websites.
In conclusion, AI generated images have come a long way and have the potential to revolutionize many industries. With advancements in deep learning and computational power, the possibilities for AI generated images are endless, and we can expect to see even more incredible breakthroughs in the near future.
DALL-E and Midjourney are the most popular and advanced technology for AI generated images. If you are excited to know more about Midjourney here is another post where we talk in details about midjourney and how to use it.
