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BigGAN: High Fidelity Image Synthesis by Nguyễn Việt is a document available to read on EtoBox.

This document summarizes a research paper that trains large-scale Generative Adversarial Networks (GANs) to generate high-fidelity natural images. The authors demonstrate that GANs benefit significantly from increased scale, training models with more parameters and larger batch sizes than prior work. They introduce architectural and regularization changes that improve scalability and conditioning, boosting performance metrics. Their "BigGAN" models set new state-of-the-art results for class-conditional imag

Author

Nguyễn Việt

Language

EN