[Reading] Names and Faces in the News Abstract

This paper propose a dataset which is more realistic than usual face recognition datasets, because it contains faces captured "in the wild" in a variety of configurations with respect to the camera, taking a variety of expressions, and under illumination of widely varying color. Each face image is associated with a set of names, automatically extracted from the associated caption. Many, but not all such sets contain the correct name.

This paper shows quite good face clustering is possible for this dataset which has inaccurately and ambiguously labelled face images. The approach used in this paper is focus on adopting the kPCA/LDA methodology, rather than on building a multi-class classifier to do face recognition.