Facial expression transfer with input-output Temporal Restricted Boltzmann Machines
Conference Paper, Proceedings of (NeurIPS) Neural Information Processing Systems, pp. 1629 - 1637, December, 2011
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.
BibTeX
@conference{Zeiler-2011-122652,author = {Matthew D. Zeiler and Graham W. Taylor and Leonid Sigal and Iain Matthews and Rob Fergus},
title = {Facial expression transfer with input-output Temporal Restricted Boltzmann Machines},
booktitle = {Proceedings of (NeurIPS) Neural Information Processing Systems},
year = {2011},
month = {December},
pages = {1629 - 1637},
}
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