Tag: autoencoder

AI Machine Learning & Data Science Research

EPFL’s Multi-modal Multi-task Masked Autoencoder: A Simple, Flexible and Effective ViT Pretraining Strategy Applicable to Any RGB Dataset

The Swiss Federal Institute of Technology Lausanne (EPFL) presents Multi-modal Multi-task Masked Autoencoders (MultiMAE), a simple and effective pretraining strategy that enables masked autoencoding to include multiple modalities and tasks and is applicable to any RGB dataset.


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.