This dataset does not exist: training models from generated images

Understand

Current generative networks are increasingly proficient in generating high-resolution realistic images.

• These generative networks, especially the conditional ones, can potentially become a great tool for providing new image datasets.
• This naturally brings the question: Can we train a classifier only on the generated data? This potential availability of nearly unlimited amounts of training data challenges standard practices for training machine learning models, which have been crafted across the years for limited and fixed size datasets.
• In this work we investigate this question and its related challenges.