A common practice in metric learning is to train and test an embedding m...
In a joint vision-language space, a text feature (e.g., from "a photo of...
Accurate solutions to the electronic Schrödinger equation can provide
va...
Supervision for metric learning has long been given in the form of
equiv...
Domain generalization is the task of learning models that generalize to
...
We consider the problem of active domain adaptation (ADA) to unlabeled t...
We present a novel self-taught framework for unsupervised metric learnin...
Deep metric learning aims to learn an embedding space where the distance...
This paper presents a novel method for embedding transfer, a task of
tra...
Existing metric learning losses can be categorized into two classes:
pai...
Metric Learning for visual similarity has mostly adopted binary supervis...