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Understanding web images by object relation network

Authors:

Viktor PrasannaAuthors Info & Claims

WWW '12: Proceedings of the 21st international conference on World Wide Web

Pages 291 - 300

https://doi.org/10.1145/2187836.2187876

Published: 16 April 2012 Publication History

Abstract

This paper presents an automatic method for understanding and interpreting the semantics of unannotated web images. We observe that the relations between objects in an image carry important semantics about the image. To capture and describe such semantics, we propose Object Relation Network (ORN), a graph model representing the most probable meaning of the objects and their relations in an image. Guided and constrained by an ontology, ORN transfers the rich semantics in the ontology to image objects and the relations between them, while maintaining semantic consistency (e.g., a soccer player can kick a soccer ball, but cannot ride it). We present an automatic system which takes a raw image as input and creates an ORN based on image visual appearance and the guide ontology. We demonstrate various useful web applications enabled by ORNs, such as automatic image tagging, automatic image description generation, and image search by image.

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Cited By

Agrawal MJalal ASharma H(2024) Enhancing scene‐text visual question answering with relational reasoning, attention and dynamic vocabulary integration Computational Intelligence10.1111/coin.1263540:1Online publication date: 20-Feb-2024
https://doi.org/10.1111/coin.12635
Jin ZWu HYang CZhou FQin JXiao LYin X(2023)RUArt: A Novel Text-Centered Solution for Text-Based Visual Question AnsweringIEEE Transactions on Multimedia10.1109/TMM.2021.312019425(1-12)Online publication date: 2023
https://doi.org/10.1109/TMM.2021.3120194
Beckh KMüller SJakobs MToborek VTan HFischer RWelke PHouben Svon Rueden L(2023)Harnessing Prior Knowledge for Explainable Machine Learning: An Overview2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)10.1109/SaTML54575.2023.00038(450-463)Online publication date: Feb-2023
https://doi.org/10.1109/SaTML54575.2023.00038
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Index Terms

Understanding web images by object relation network
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

cover image ACM Other conferences

WWW '12: Proceedings of the 21st international conference on World Wide Web

April 2012

1078 pages

ISBN:9781450312295

DOI:10.1145/2187836

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Univ. de Lyon: Universite de Lyon

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

Sponsor:

Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Agrawal MJalal ASharma H(2024) Enhancing scene‐text visual question answering with relational reasoning, attention and dynamic vocabulary integration Computational Intelligence10.1111/coin.1263540:1Online publication date: 20-Feb-2024
https://doi.org/10.1111/coin.12635
Jin ZWu HYang CZhou FQin JXiao LYin X(2023)RUArt: A Novel Text-Centered Solution for Text-Based Visual Question AnsweringIEEE Transactions on Multimedia10.1109/TMM.2021.312019425(1-12)Online publication date: 2023
https://doi.org/10.1109/TMM.2021.3120194
Beckh KMüller SJakobs MToborek VTan HFischer RWelke PHouben Svon Rueden L(2023)Harnessing Prior Knowledge for Explainable Machine Learning: An Overview2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)10.1109/SaTML54575.2023.00038(450-463)Online publication date: Feb-2023
https://doi.org/10.1109/SaTML54575.2023.00038
Elahi EIglesias AMorato J(2022)Readability of Graphical Contents on World Wide Web (WWW)2022 17th Iberian Conference on Information Systems and Technologies (CISTI)10.23919/CISTI54924.2022.9820011(1-4)Online publication date: 22-Jun-2022
https://doi.org/10.23919/CISTI54924.2022.9820011
Elahi EIglesias AMorato J(2022)Web Images Relevance and Quality: User EvaluationProceedings of the 5th International Conference on Computer Science and Software Engineering10.1145/3569966.3569984(66-69)Online publication date: 21-Oct-2022
https://dl.acm.org/doi/10.1145/3569966.3569984
He YGarg RChowdhury A(2022)TD-Road: Top-Down Road Network Extraction with Holistic Graph ConstructionComputer Vision – ECCV 202210.1007/978-3-031-20077-9_33(562-577)Online publication date: 6-Nov-2022
https://doi.org/10.1007/978-3-031-20077-9_33
Elahi ELara JMaqueda A(2022)Image Relevance on Websites and ReadabilityInformation Systems and Technologies10.1007/978-3-031-04826-5_28(286-295)Online publication date: 11-May-2022
https://doi.org/10.1007/978-3-031-04826-5_28
Liu MWang HLi YBian Y(2020)Research on Visual Relation Detection Based on Computer Vision2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)10.1109/AEMCSE50948.2020.00080(342-345)Online publication date: Apr-2020
https://doi.org/10.1109/AEMCSE50948.2020.00080
Donadello ISerafini L(2019)Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image Interpretation2019 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2019.8852413(1-8)Online publication date: Jul-2019
https://doi.org/10.1109/IJCNN.2019.8852413
Zhang JWang ZMu YWang Z(2019)Image region label refinement using spatial position relation graphKnowledge-Based Systems10.1016/j.knosys.2018.12.010166(82-91)Online publication date: Feb-2019
https://doi.org/10.1016/j.knosys.2018.12.010
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