Authors
Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, Tomas Mikolov
Publication date
2013
Conference
Advances in neural information processing systems
Pages
2121-2129
Description
Abstract Modern visual recognition systems are often limited in their ability to scale to large
numbers of object categories. This limitation is in part due to the increasing difficulty of
acquiring sufficient training data in the form of labeled images as the number of object
categories grows. One remedy is to leverage data from other sources--such as text data--
both to train visual models and to constrain their predictions. In this paper we present a new
deep visual-semantic embedding model trained to identify visual objects using both ...
Total citations
201320142015201643811292
Scholar articles
A Frome, GS Corrado, J Shlens, S Bengio, J Dean… - Advances in neural information processing systems, 2013