Skip navigation.

UCSD Computer Vision

Steve Branson, PhD Student






Projects


Similarity Metrics for Categorization: from Monolithic to Category Specific

Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjunction with a nearest neighbor classifier, or can be plugged in as kernels to an SVM. For the task of categorization two s...




Publications


2009
Babenko B., Branson S., Belongie S., "Similarity Functions for Categorization: from Monolithic to Category Specific ", International Conference on Computer Vision (ICCV), Kyoto, Japan, 2009. [BibTex][pdf]