Improved-GAN is the official code release from OpenAI accompanying the research paper Improved Techniques for Training GANs. It provides implementations of experiments conducted on datasets such as MNIST, SVHN, CIFAR-10, and ImageNet. The project focuses on demonstrating enhanced training methods for Generative Adversarial Networks, addressing stability and performance issues that were common in earlier GAN models. The repository includes training scripts, evaluation methods, and pretrained configurations for reproducing experimental results. By offering structured experiments across multiple datasets, it allows researchers to study and replicate the improvements described in the paper. Although the project is archived and not actively maintained, it remains a reference point in the history of GAN research, influencing subsequent model training approaches.
Features
- Implementations of GAN training with improved techniques
- Support for MNIST, SVHN, CIFAR-10, and ImageNet datasets
- Code for reproducing experimental results from the paper
- Training scripts demonstrating stability improvements
- Evaluation tools including Inception Score metrics
- Archived reference implementation for GAN research