We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
We introduce a generic structure-from-motion approach based on a previously introduced, highly general imaging model, where cameras are modeled as possibly unconstrained sets of p...
Srikumar Ramalingam, Suresh K. Lodha, Peter F. Stu...
This research is based on the realization that the desktop computing paradigm is not appropriate for television, because it is adapted to fundamentally different user aspirations ...
As part of a more extensive study of reading-related practices, we have explored how people share information they encounter in their everyday reading as a complement to the more ...
We describe a directed bilinear model that learns higherorder groupings among features of natural images. The model represents images in terms of two sets of latent variables: one...
Jack Culpepper, Jascha Sohl-Dickstein, Bruno Olaha...