Classification is a Strong Baseline for Deep Metric Learning

Understand

Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images.

• Two major applications of metric learning are content-based image retrieval and face verification.
• For the retrieval tasks, the majority of current state-of-the-art (SOTA) approaches are triplet-based non-parametric training.
• For the face verification tasks, however, recent SOTA approaches have adopted classification-based parametric training.