sheqi/GAN_Review
A Survey and Taxonomy of the Recent GANs Development，computer vision & time series
This resource provides a comprehensive overview and classification of Generative Adversarial Networks (GANs) tailored for both computer vision and time series applications. It helps researchers, practitioners, and students understand the landscape of GAN models by detailing various architectures and loss functions. The output is a structured understanding of GAN development, enabling informed choices for tasks like image generation, data augmentation, or synthetic time series creation.
443 stars. No commits in the last 6 months.
Use this if you are a researcher or practitioner in machine learning, interested in understanding the current state and taxonomy of GANs for generating realistic images or synthetic time series data.
Not ideal if you are looking for a plug-and-play tool or a software library to directly implement GANs without understanding the underlying research and model variations.
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Aug 14, 2021
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