We perceive the shapes and material properties of objects quickly and reliably despite the
complexity and objective ambiguities of natural images. Typical images are highly complex …

The human visual system is the most complex pattern recognition device known. In ways
that are yet to be fully understood, the visual cortex arrives at a simple and unambiguous …

Crowdsourcing has emerged as a novel problem-solving paradigm, which facilitates
addressing problems that are hard for computers, eg, entity resolution and sentiment …

We show that a generative random field model, which we call generative ConvNet, can be
derived from the commonly used discriminative ConvNet, by assuming a ConvNet for multi …

Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

This book provides a self-contained and up-to-date treatment of the Monte Carlo method
and develops a common framework under which various Monte Carlo techniques can be" …

With the advent of the Internet, billions of images are now freely available online and
constitute a dense sampling of the visual world. Using a variety of non-parametric methods …

We present a universal statistical model for texture images in the context of an overcomplete
complex wavelet transform. The model is parameterized by a set of statistics computed on …

Inpainting is an image interpolation problem, often referring to interpolations over large-
scale missing domains. In this paper, guided by the connectivity principle of human visual …