Open Access

REVIEW

A Survey of GAN Based Image Synthesis

Jiahe Ni^*

Engineering Research Center of Digital Forensics of Ministry of Education, School of Computer, Nanjing University of Information Science & Technology, Nanjing, 210044, China

* Corresponding Author: Jiahe Ni. Email:

Journal of Information Hiding and Privacy Protection 2022, 4(2), 79-88. https://doi.org/10.32604/jihpp.2022.039751

Received 01 February 2023; Accepted 06 March 2023; Issue published 17 April 2023

Abstract

Image generation is a hot topic in the academic recently, and has been applied to AI drawing, which can bring Vivid AI paintings without labor costs. In image generation, we represent the image as a random vector, assuming that the images of the natural scene obey an unknown distribution, we hope to estimate its distribution through some observation samples. Especially, with the development of GAN (Generative Adversarial Network), The generator and discriminator improve the model capability through adversarial, the quality of the generated image is also increasing. The image quality generated by the existing GAN based image generation model is so well-paint that it can be passed for genuine one. Based on the brief introduction of the concept of GAN, this paper analyzes the main ideas of image synthesis, studies the representative SOTA GAN based Image synthesis method.

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Keywords

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