Learning a Tree of Metrics with Disjoint Visual Features

@inproceedings{Hwang2011LearningAT,
  title={Learning a Tree of Metrics with Disjoint Visual Features},
  author={Sung Ju Hwang and Kristen Grauman and Fei Sha},
  booktitle={NIPS},
  year={2011}
}
We introduce an approach to learn discriminative visual representations while exploiting external semantic knowledge about object category relationships. Given a hierarchical taxonomy that captures semantic similarity between the objects, we learn a corresponding tree of metrics (ToM). In this tree, we have one metric for each non-leaf node of the object hierarchy, and each metric is responsible for discriminating among its immediate subcategory children. Specifically, a Mahalanobis metric… CONTINUE READING
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