Abstract. Analysis of shape variability is important for diagnostic classification and understanding of biological processes. We present a novel shape analysis approach based on a ...
Paul A. Yushkevich, Stephen M. Pizer, Sarang C. Jo...
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
Models of activity structure for unconstrained environments are generally not available a priori. Recent representational approaches to this end are limited by their computational...
Raffay Hamid, Siddhartha Maddi, Aaron F. Bobick, I...
In 3D face recognition systems, 3D facial shape information plays an important role. 3D face recognizers usually depend on point cloud representation of faces where faces are repre...
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle