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Understanding visual scenes

Published online by Cambridge University Press:  28 March 2018

CARINA SILBERER ,
JASPER UIJLINGS  and
MIRELLA LAPATA
CARINA SILBERER
Affiliation:
DTCL, Universitat Pompeu Fabra, Roc Boronat 138, 08018 Barcelona, Spain e-mail: [email protected]
JASPER UIJLINGS
Affiliation:
School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, EH8 9AB, UK e-mail: [email protected]
MIRELLA LAPATA
Affiliation:
ILCC, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, EH8 9AB, UK e-mail: [email protected]
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Abstract

A growing body of recent work focuses on the challenging problem of scene understanding using a variety of cross-modal methods which fuse techniques from image and text processing. In this paper, we develop representations for the semantics of scenes by explicitly encoding the objects detected in them and their spatial relations. We represent image content via two well-known types of tree representations, namely constituents and dependencies. Our representations are created deterministically, can be applied to any image dataset irrespective of the task at hand, and are amenable to standard NLP tools developed for tree-based structures. We show that we can apply syntax-based SMT and tree kernel methods in order to build models for image description generation and image-based retrieval. Experimental results on real-world images demonstrate the effectiveness of the framework.

Type
Articles
Information
Natural Language Engineering , Volume 24 , Special Issue 3: Language for Images , May 2018 , pp. 441 - 465
Copyright
Copyright © Cambridge University Press 2018 

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