We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
This paper explores a formulation for attributed graph matching as an inference problem over a hidden Markov Random Field. We approximate the fully connected model with simpler mo...
Dante Augusto Couto Barone, Terry Caelli, Tib&eacu...
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
This paper presents GeoS, a new algorithm for the efficient segmentation of n-dimensional image and video data. The segmentation problem is cast as approximate energy minimization ...
In this paper, we present a new method to change the illumination condition of a face image, with unknown face geometry and albedo information. This problem is particularly diffic...
Yang Wang, Zicheng Liu, Gang Hua, Zhen Wen, Zhengy...