Deep metric learning using Triplet network

Code

• github.com/eladhoffer/TripletNet
  torch★ 187
• github.com/jjmachan/DeepHash
  pytorch★ 0
• github.com/Ariel-Perez/triplet-net
  tf★ 0

Abstract

Deep learning has proven itself as a successful set of models for learning useful semantic representations of data. These, however, are mostly implicitly learned as part of a classification task. In this paper we propose the triplet network model, which aims to learn useful representations by distance comparisons. A similar model was defined by Wang et al. (2014), tailor made for learning a ranking for image information retrieval. Here we demonstrate using various datasets that our model learns a better representation than that of its immediate competitor, the Siamese network. We also discuss future possible usage as a framework for unsupervised learning.

Tasks

Reproductions