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The GAN Zoo is an open-source repository that compiles a comprehensive list of Generative Adversarial Network models published in research literature. The project began as a community effort to track the rapidly growing number of GAN architectures appearing in machine learning papers. Because new GAN models are frequently introduced in research publications, the repository serves as a convenient catalog that organizes them in one location. The list includes references to many GAN variants along with links to their original research papers and sometimes implementation code. Users can browse the dataset or explore a tabular version that allows filtering by year or searching for specific model names. The repository encourages contributions from the community so that newly published GAN architectures can be added to the list.
Features
- Catalog of named Generative Adversarial Network architectures
- Links to research papers describing each GAN model
- Searchable dataset of GAN models organized by year
- Community contributions for adding new GAN variants
- Tabular dataset format enabling filtering and browsing
- Reference resource for researchers studying generative models
Project Samples
