A Neural Network to Retrieve Images from Text Queries
This work presents a neural network for the retrieval of images from text queries. The proposed network is composed of two main modules: the first one extracts a global picture representation from local block descriptors while the second one aims at solving the retrieval problem from the extracted representation. Both modules are trained jointly to minimize a loss related to the retrieval performance. This approach is shown to be advantageous when compared to previous models relying on unsupervised feature extraction: average precision over Corel queries reaches 26.2% for our model, which should be compared to 21.6% for PAMIR, the best alternative.
- URL: http://publications.idiap.ch/downloads/reports/2006/grangier_icann06.pdf
- Related documents: http://publications.idiap.ch/index.php/publications/showcite/grangier:2006:idiap-06-33
Record created on 2010-02-11, modified on 2016-08-08