MetricFormer

Similarity learning can be significantly advanced by informative relationships among different samples and features. The current methods try to excavate the multiple correlations indifferent aspects, butcannot integratethemintoaunified framework. In this paper,we provide to consider the multiple correlations from a unified perspective and propose a new method called MetricFormer, which can effectively capture and model the multiple correlations with an elaborate metric transformer.