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...
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality of the input is low. For complex and high-dimensio...
Gregory Shakhnarovich, Paul A. Viola, Trevor Darre...
This paper describes a novel approach to automatically recover corresponding feature points and epipolar geometry over two wide baseline frames. Our contributions consist of sever...
In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...