Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...
Images magnified by standard methods display a degradation of detail that is particularly noticeable in the blurry edges of text. Current super-resolution algorithms address the l...
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
Face hallucination is to reconstruct a high-resolution face image from a low-resolution one based on a set of high- and low-resolution training image pairs. This paper proposes an ...
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...