This repository is a curated list of open-source projects leveraging machine learning for synthetic content generation, targeting researchers and developers interested in AI-driven content creation. It provides a categorized overview of tools and models for generating realistic synthetic data across various modalities like images, text, and more.

How It Works

The project functions as a directory, linking to external repositories and resources that implement specific synthetic content generation techniques. It highlights projects utilizing Generative Adversarial Networks (GANs) for image synthesis, such as NVIDIA's StyleGAN, and large language models for text generation. The curation focuses on projects demonstrating novel approaches to creating diverse and high-quality synthetic data.

Highlighted Details

• Categorized list of projects for synthetic images (faces, cats, anime, shoes) and text (lyrics, quotes, resumes, game reviews).
• Includes links to foundational research papers and codebases like NVIDIA's Progressive Growing of GANs and StyleGAN.
• Features projects for interactive generation of art and faces, as well as procedural generation of startup ideas.
• Provides links to resources for contributing and expanding the curated list.

Maintenance & Community

The project is maintained by paulbricman. Contributions are welcomed via pull requests, with guidelines provided for submission.

Licensing & Compatibility

The licensing for individual projects linked within this list varies. Users must consult the licenses of each external repository for specific usage rights and compatibility.

Limitations & Caveats

This repository is a curated list and does not host any code itself. The functionality, maintenance, and licensing depend entirely on the external projects linked.