Generative adversarial networks (GANs) generate high-dimensional vector spaces (latent
spaces) that can interchangeably represent vectors as images. Advancements have
extended their ability to computationally generate images indistinguishable from real images
such as faces, and more importantly, to manipulate images using their inherit vector values
in the latent space. This interchangeability of latent vectors has the potential to calculate not
only the distance in the latent space, but also the human perceptual and cognitive distance …

Generative adversarial networks (GANs) generate high-dimensional vector spaces (latent
spaces) that can interchangeably represent vectors as images. Advancements have
extended their ability to computationally generate images indistinguishable from real images
such as faces, and more importantly, manipulate images using their inherit vector values in
the latent space. This interchangeability of latent vector has the potential to calculate not
only distance in the latent space, but also human perceptual and cognitive distance toward …