CNNs have been phenomenal in computer vision tasks, be it for classifying images or detecting objects in images. CNNs were so good at understanding images that they inspired researchers to use CNNs in a GAN network. Initially, authors of the official GAN paper introduced Deep Neural Networks (DNNs) with dense layers only. Convolutional layers were not used in the original implementation of the GAN network. In the previous GANs, the generator and the discriminator network used dense hidden layers only. Instead, authors suggested that different neural network architectures can be used in a GAN setup.
DCGANs extend the idea of using convolutional layers in the discriminator and the generator network. The setup of a DCGAN is similar to a vanilla GAN. It consists of two networks: a generator and a discriminator. The generator is a DNN with convolutional layers...
