A Comprehensive Survey of Scene Graphs: Generation and Application.

Chang, X; Ren, P; Xu, P; Li, Z; Chen, X; Hauptmann, AG

A Comprehensive Survey of Scene Graphs: Generation and Application.

Chang, X

Ren, P Xu, P Li, Z Chen, X Hauptmann, AG

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45, (1), pp. 1-26
Issue Date:: 2023-12-23

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Field	Value	Language
dc.contributor.author	Chang, X https://orcid.org/0000-0002-7778-8807
dc.contributor.author	Ren, P
dc.contributor.author	Xu, P
dc.contributor.author	Li, Z
dc.contributor.author	Chen, X
dc.contributor.author	Hauptmann, AG
dc.date.accessioned	2023-03-31T04:47:29Z
dc.date.available	2023-03-31T04:47:29Z
dc.date.issued	2023-12-23
dc.identifier.citation	IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45, (1), pp. 1-26
dc.identifier.issn	0162-8828
dc.identifier.issn	1939-3539
dc.identifier.uri	http://hdl.handle.net/10453/168932
dc.description.abstract	Scene graph is a structured representation of a scene that can clearly express the objects, attributes, and relationships between objects in the scene. As computer vision technology continues to develop, people are no longer satisfied with simply detecting and recognizing objects in images; instead, people look forward to a higher level of understanding and reasoning about visual scenes. For example, given an image, we want to not only detect and recognize objects in the image, but also know the relationship between objects (visual relationship detection), and generate a text description (image captioning) based on the image content. Alternatively, we might want the machine to tell us what the little girl in the image is doing (Visual Question Answering (VQA)), or even remove the dog from the image and find similar images (image editing and retrieval), etc. These tasks require a higher level of understanding and reasoning for image vision tasks. The scene graph is just such a powerful tool for scene understanding. Therefore, scene graphs have attracted the attention of a large number of researchers, and related research is often cross-modal, complex, and rapidly developing. However, no relatively systematic survey of scene graphs exists at present.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation	http://purl.org/au-research/grants/arc/DE190100626
dc.relation.ispartof	IEEE Transactions on Pattern Analysis and Machine Intelligence
dc.relation.isbasedon	10.1109/TPAMI.2021.3137605
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0806 Information Systems, 0906 Electrical and Electronic Engineering
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	A Comprehensive Survey of Scene Graphs: Generation and Application.
dc.type	Journal Article
utslib.citation.volume	45
utslib.location.activity	United States
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0806 Information Systems
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	in_progress	*
pubs.consider-herdc	false
dc.date.updated	2023-03-31T04:47:24Z
pubs.issue	1
pubs.publication-status	Published online
pubs.volume	45
utslib.citation.issue	1

Abstract:

Scene graph is a structured representation of a scene that can clearly express the objects, attributes, and relationships between objects in the scene. As computer vision technology continues to develop, people are no longer satisfied with simply detecting and recognizing objects in images; instead, people look forward to a higher level of understanding and reasoning about visual scenes. For example, given an image, we want to not only detect and recognize objects in the image, but also know the relationship between objects (visual relationship detection), and generate a text description (image captioning) based on the image content. Alternatively, we might want the machine to tell us what the little girl in the image is doing (Visual Question Answering (VQA)), or even remove the dog from the image and find similar images (image editing and retrieval), etc. These tasks require a higher level of understanding and reasoning for image vision tasks. The scene graph is just such a powerful tool for scene understanding. Therefore, scene graphs have attracted the attention of a large number of researchers, and related research is often cross-modal, complex, and rapidly developing. However, no relatively systematic survey of scene graphs exists at present.

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http://hdl.handle.net/10453/168932