论文标题
指标学习现实检查
A Metric Learning Reality Check
论文作者
论文摘要
过去四年来的深度度量学习论文一直声称准确性取得了长足的进步，通常使十年历史的方法的性能翻了一番。在本文中，我们仔细研究了该领域，以查看这是否真的是正确的。我们发现众多公制学习论文的实验方法中存在缺陷，并表明随着时间的推移，实际的改进充其量至少是微不足道的。
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.
