Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines

Part of Advances in Neural Information Processing Systems 24 (NIPS 2011)

Bibtex Metadata Paper

Authors

Matthew Zeiler, Graham W. Taylor, Leonid Sigal, Iain Matthews, Rob Fergus

Abstract

We present a type of Temporal Restricted Boltzmann Machine that defines a probability distribution over an output sequence conditional on an input sequence. It shares the desirable properties of RBMs: efficient exact inference, an exponentially more expressive latent state than HMMs, and the ability to model nonlinear structure and dynamics. We apply our model to a challenging real-world graphics problem: facial expression transfer. Our results demonstrate improved performance over several baselines modeling high-dimensional 2D and 3D data.