ABSTRACT. Previous work on unsupervised learning has shown that it is possible to learn Gabor-like feature representations, similar to those employed in the ...
Goal: Find a set of basis functions {φi} for representing natural images such that the coefficients ai are as sparse and statistically independent as possible.
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We present results demonstrating bilinear sparse coding of natural images. We also explore an extension of the model that can capture spatial relationships ...
We present results demonstrating bilinear sparse coding of natural images. We also explore an extension of the model that can capture spatial relationships ...
To render an image of a particular person in a particular pose, a set of I × J basis images wij is linearly mixed with coefficients given by the tensor product ...
Our images are simple compared to natural images but contain sufficient ... within three-dimensional linear models of natural surfaces and illuminants.
redundan y in the image ode and provides a basis for transformation- invariant vision. We present results demonstrating bilinear sparse oding of natural images.
This paper proposes a novel deep learning model called bilinear deep belief network (BDBN) for image classification. Unlike previous image classification models ...
This paper proposes Bilinear Active Appearance Models. (BAAMs), an extension of AAMs, that effectively decouple changes due to pose and expression/identity. We ...