Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
The mammalian visual system is one of the most intensively investigated sensory systems. However, our knowledge of the typical input it is operating on is surprisingly limited. To ...
We seek a framework that addresses localization, detection and recognition of man-made objects in natural-scene images in a unified manner. We propose to model artificial structur...
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...