StyleGAN (Style Generative Adversarial Network)
A generative model architecture called StyleGAN (Style Generative Adversarial Network) was created specifically for the purpose of image synthesis.
An upgrade to the original GAN (Generative Adversarial Network) architecture, StyleGAN is renowned for producing a wide range of realistic and high-quality synthetic images.
Key Features of StyleGAN (Style Generative Adversarial Network)
- Generative Adversarial Network (GAN): StyleGAN is built upon the GAN framework, which consists of a generator and a discriminator.
- Open Source Implementation: NVIDIA released the source code for StyleGAN, making it available to the research and developer community.
- Application to Faces and Art: While StyleGAN is a general-purpose generative model, it gained significant attention for its ability to generate highly realistic faces.
Applications of StyleGAN (Style Generative Adversarial Network)
- Deepfake production
- Virtual fashion design
- Artistic image generating, and other creative applications.
Benefits: Generates realistic details in high-resolution, aesthetically pleasing photographs.
Top Generative AI Models to Explore in 2024
Generative AI models have become potent instruments in the rapidly changing field of artificial intelligence, capable of producing original texts, visuals, and even whole stories. By 2024, generative AI will have advanced to never-before-seen levels thanks to a variety of models that are pushing the envelope in terms of originality and inventiveness.
These Generative AI Models demonstrate the breadth and depth of applications for Generative AI, ranging from language production to image synthesis. While some models are quite good at producing text that seems human, others produce realistic and beautiful visuals. Every model offers a different set of advantages and a window into the seemingly endless possibilities of AI-driven creation.
In this article, we’ll be looking into 9 distinct AI generative, segmented into Text, Image, and Code generative AIs. Before getting into the Top generative AI models, let’s first understand in brief what is generative AI.