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Visualizing deep convolutional neural networks using natural pre-images

Abstract:

Image representations, from SIFT and bag of visual words to convolutional neural networks (CNNs) are a crucial component of almost all computer vision systems. However, our understanding of them remains limited. In this paper we study several landmark representations, both shallow and deep, by a number of complementary visualization techniques. These visualizations are based on the concept of “natural pre-image”, namely a natural-looking image whose representation has some notable property. W...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s11263-016-0911-8

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
Springer Verlag
Journal:
International Journal of Computer Vision More from this journal
Volume:
120
Issue:
3
Pages:
233-255
Publication date:
2016-05-18
Acceptance date:
2016-04-15
DOI:
EISSN:
1573-1405
ISSN:
0920-5691
Keywords:
Pubs id:
pubs:624524
UUID:
uuid:23d4558c-45b6-4c30-9b6a-288a7fef3ab9
Local pid:
pubs:624524
Source identifiers:
624524
Deposit date:
2016-05-27

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