Tag: Generative Adversarial Network

AI Computer Vision & Graphics Machine Learning & Data Science Research

House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation

This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture.

Research

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.