Abstract. We propose a new method for face recognition under arbitrary pose and illumination conditions, which requires only one training image per subject. Furthermore, no limitat...
Abstract. A common practice to gain invariant features in object recognition models is to aggregate multiple low-level features over a small neighborhood. However, the differences ...
Browsers do not currently support the secure sharing of JavaScript objects between principals. We present this problem as the need for object views, which are consistent and contr...
Leo A. Meyerovich, Adrienne Porter Felt, Mark S. M...
This work proposes a learning method for deep architectures that takes advantage of sequential data, in particular from the temporal coherence that naturally exists in unlabeled v...
Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...