Introduction to Multiple Random Window Discriminator in GAN-TTS
Multiple Random Window Discriminator (MRWD) is a part of the GAN-TTS text-to-speech architecture that evaluates audio in different ways. MRWD operates on randomly sub-sampled fragments of real or generated samples, which allows data augmentation and reduces computational complexity. The ensemble allows for the evaluation of audio in different complementary ways and yields ten discriminators by taking the Cartesian product of two pa
NIMA: Enhancing Perceptual Quality of Images
When it comes to image enhancement, the goal is to improve the quality of the image while maintaining the original visual intent of the content. This requires techniques that are both focused on enhancing the technical details of the image, as well as improving its perceptual quality. One approach to achieving this is through the use of a tool called NIMA, which stands for Neural Image Assessment.
NIMA is a deep learning model that is designed to pr
What is PatchGAN?
PatchGAN is a type of discriminator for generative adversarial networks (GAN), a type of deep learning model used for image generation. A GAN consists of two neural networks: a generator and a discriminator. The generator creates images, while the discriminator checks whether the generated images are real or fake. This process continues until the generator is able to produce images that the discriminator cannot distinguish from real ones.
PatchGAN is a specific type of discri
A Projection Discriminator is a type of discriminator used in generative adversarial networks (GANs). In GANs, the discriminator is responsible for distinguishing between real and fake data generated by the generator. The Projection Discriminator is motivated by a probabilistic model where the distribution of the conditional variable y given x is either a discrete or uni-modal continuous distribution.
Understanding the Loss Function in GANs
To understand the Projection Discriminator, it's imp
SESAME Discriminator Overview
SESAME Discriminator is a tool designed to enhance layout2image generation by extending PatchGAN Discriminator. It is a system that provides an improved quality of images through the fusion of two processing stream of RGB images and semantics.
When it comes to layout2image generation, the quality of images and their details matter a lot. The SESAME Discriminator is designed specifically to improve this quality by creating a more sophisticated model than the PatchG
Overview of Window-based Discriminator
Window-based Discriminator is a type of discriminator for generative adversarial networks that is designed to classify between distributions of small audio chunks. This method is analogous to a PatchGAN but is specifically created for audio. The aim of a window-based discriminator is to maintain coherence of audio signal across patches. In this article we will discuss what is a discriminator, what is a generative adversarial network, how a window-based dis