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University of Cambridge > Talks.cam > Microsoft Research Cambridge, public talks > Generative Models for Shape and Appearance
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If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins. This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending I will present recent work from SIGGRAPH and CVPR . The first builds a generative model of fonts in an automatic and unsupervised learning process; the only input is a collection of existing font files and the output is a probabilistic manifold that can be used to create new typefaces. The second piece of work generalises probabilistic PCA and Active Appearance Models to overcome a fundamental weakness; existing subspace models are unable to model image datasets that cannot be readily aligned. Instead, we learn a subspace model in a new context space, a deterministic function of an input “part map”, that implicitly encodes correspondence and thus brings the data into alignment. We illustrate the value of this approach by considering two example tasks: structured in-painting and appearance transfer. This talk is part of the Microsoft Research Cambridge, public talks series. This talk is included in these lists:
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