We develop an object classification method that can learn a novel class from a single training example. In this method, experience with already learned classes is used to facilita...
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
The objective of this work is to recognize all the frontal faces of a character in the closed world of a movie or situation comedy, given a small number of query faces. This is ch...
We propose using simple mixture models to define a set of mid-level binary local features based on binary oriented edge input. The features capture natural local structures in the...
We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of categories is very large an...