Edit any face -- Image Synthesis using GAN’s
Sarthak Mishra, Parthak Mehta, Nikhil Chouhan, Neel Pethani, Ishani Saha · 2022
In recent years, Generative Adversarial Networks (GANs) have become a hot topic among researchers and engineers that work with deep learning. Generative Adversarial Networks (GANs) are a class of generative models that were introduced in 2014 by Ian Goodfellow et al [1]. It has been a ground-breaking technique which can generate new pieces of content of data in a consistent way. The topic of GANs has exploded in popularity due to its applicability in fields like image generation and synthesis, and music production and composition. GANs have two competing neural networks: a generator and a discriminator.We talk about 2 major use case implementations of GANs in this paper – Face Attribute Editing and Motion Copy.