Learning a similarity metric discriminatively, with application to face verification


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 and not known during training, and where the number of training samples for a single category is very small. The idea is to learn a function that maps input patterns into a target… (More)
DOI: 10.1109/CVPR.2005.202


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