UGQE: Uncertainty Guided Query Expansion

Firat Oncel*, Mehmet Aygün, Gulcin Baykal, Gozde Unal

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Query expansion is a standard technique in image retrieval, which enriches the original query by capturing various features from relevant images and further aggregating these features to create an expanded query. In this work, we present a new framework, which is based on incorporating uncertainty estimation on top of a self attention mechanism during the expansion procedure. An uncertainty network provides added information on the images that are relevant to the query, in order to increase the expressiveness of the expanded query. Experimental results demonstrate that integrating uncertainty information into a transformer network can improve the performance in terms of mean Average Precision (mAP) on standard image retrieval datasets in comparison to existing methods. Moreover, our approach is the first one that incorporates uncertainty in aggregation of information in a query expansion procedure.

Original languageEnglish
Title of host publicationPattern Recognition and Artificial Intelligence - 3rd International Conference, ICPRAI 2022, Proceedings
EditorsMounîm El Yacoubi, Eric Granger, Pong Chi Yuen, Umapada Pal, Nicole Vincent
PublisherSpringer Science and Business Media Deutschland GmbH
Pages109-120
Number of pages12
ISBN (Print)9783031090363
DOIs
Publication statusPublished - 2022
Event3rd International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022 - Paris, France
Duration: 1 Jun 20223 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13363 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022
Country/TerritoryFrance
CityParis
Period1/06/223/06/22

Bibliographical note

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Keywords

  • Image retrieval
  • Self attention
  • Uncertainty

Fingerprint

Dive into the research topics of 'UGQE: Uncertainty Guided Query Expansion'. Together they form a unique fingerprint.

Cite this