Tag: Generative Adversarial Network

AI Machine Learning & Data Science Research

Leibniz University Hannover Proposes World-GAN: A 3D GAN for Minecraft Level Generation

A research team from Leibniz University Hannover introduces World-GAN, a 3D generative adversarial network that aims to learn and generate structures directly in the 3D voxel space in Minecraft.


PixelGAN Autoencoders

PixelGAN is an autoencoder for which the generative path is a convolutional autoregressive neural network on pixels, conditioned on a latent code, and the recognition path uses a generative adversarial network (GAN) to impose a prior distribution on the latent code.