From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...
Unknown words are a major issue for large-scale grammars of natural language. We propose a machine learning based algorithm for acquiring lexical entries for all forms in the para...
Abstract People typically move and act under the constraints of an environment, making human behavior strongly place-dependent. Motion patterns, the places and the rates at which p...
Matthias Luber, Gian Diego Tipaldi, Kai Oliver Arr...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its highresolution counterpart using...