In style-constrained classification often there are only a few samples of each style and class, and the correspondences between styles in the training set and the test set are un...
In this paper we propose a series of novel morphological operators that are anisotropic, and adapt themselves to the local orientation in the image. This new morphology is therefor...
While conditional random fields (CRFs) have been applied successfully in a variety of domains, their training remains a challenging task. In this paper, we introduce a novel trai...
Lin Liao, Tanzeem Choudhury, Dieter Fox, Henry A. ...
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...