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A Metric Learning Reality Check

2020-03-18ECCV 2020Code Available1· sign in to hype

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

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Abstract

Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods. In this paper, we take a closer look at the field to see if this is actually true. We find flaws in the experimental methodology of numerous metric learning papers, and show that the actual improvements over time have been marginal at best.

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