Generative Adversarial Network Technologies and Applications in Computer Vision

Table 1

Development of GANs.

Stages	Stage 1	Stage 2	Stage 3
Time	2014.06–2015.11	2015.11–2017.01	2017.1-today
GAN models	GAN- > DCGAN	DCGAN- > WGAN	WGAN- > today
Improvements	GAN is the beginning of generating the adversarial model	DCGAN uses many new methods to make the model more stable such as batchnorm, ReLU, and leaky ReLU	WGAN uses weight clipping solving the problem of gradient disappearance