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Discovering class-specific pixels for weakly-supervised semantic segmentation

Abstract:

We propose an approach to discover class-specific pixels for the weakly-supervised semantic segmentation task. We show that properly combining saliency and attention maps allows us to obtain reliable cues capable of significantly boosting the performance. First, we propose a simple yet powerful hierarchical approach to discover the classagnostic salient regions, obtained using a salient object detector, which otherwise would be ignored. Second, we use fully convolutional attention maps to rel...

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Publication status:
Not published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Authors


Chaudhry, A More by this author
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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Rhodes Trust More from this funder
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Grant:
ERC-2012-AdG 321162- HELIOS
Acceptance date:
2017-09-05
Pubs id:
pubs:815240
URN:
uri:ffefcaeb-5b9c-41ff-a9ba-b708b9447d2f
UUID:
uuid:ffefcaeb-5b9c-41ff-a9ba-b708b9447d2f
Local pid:
pubs:815240

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