This repository is a curated list of papers, code, tutorials, and other resources related to Generative Adversarial Networks (GANs). It serves as a comprehensive reference for researchers and practitioners interested in GANs, covering theoretical foundations, various applications in computer vision and other domains, and practical implementation details.

How It Works

The repository organizes a vast collection of GAN-related research papers, categorized by topic (Theory & Machine Learning, Applied Vision, Applied Other) and resource type (Recommendations, Workshops, Tutorials, Blogs, Videos, Code). It aims to provide a structured overview of the GAN landscape, highlighting key advancements and practical implementations.

Quick Start & Requirements

This is a curated list, not a software package. No installation or execution is required.

Highlighted Details

• Extensive collection of over 300 research papers with arXiv links.
• Includes links to code repositories, tutorials, blogs, and videos for practical learning.
• Covers a wide range of GAN applications, from image generation and translation to text synthesis and music generation.
• Features a dedicated section for "Humor" with "Stopping GAN Violence: Generative Unadversarial Networks."

Maintenance & Community

The list was maintained by Holger Caesar until November 2017. While no new papers are being added, the creator invites others to continue the effort and reuse the list. Contact information for the maintainer is provided.

Licensing & Compatibility

The repository itself is a list of links and does not have a specific license. Individual linked resources (papers, code) are subject to their own licenses.

Limitations & Caveats

The repository is no longer actively updated with new papers as of November 2017, meaning it does not reflect the latest advancements in GAN research. The maintainer notes that an exhaustive list is no longer feasible.