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Affinity attention graph neural network for weakly supervised semantic segmentation

Abstract:

Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmentation, i.e., training accurate semantic segmentation models using bounding box annotations as supervision. To this end, we propose Affinity Attention Graph Neural Network (A2GNN). Following previous practices, we first generate pseudo semantic-aware seeds, which are then formed into semantic graphs based on our newly...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TPAMI.2021.3083269

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Institution:
University of Oxford
Department:
ENGINEERING SCIENCE
Sub department:
Engineering Science
Role:
Author
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Name:
Engineering and Physical Sciences Research Council
Funder identifier:
http://dx.doi.org/10.13039/501100000266
Grant:
EP/T028572/1
EP/M013774/1
Publisher:
IEEE
Journal:
IEEE Transactions on Pattern Analysis and Machine Intelligence More from this journal
Publication date:
2021-05-25
Acceptance date:
2021-05-20
DOI:
EISSN:
1939-3539
ISSN:
0162-8828
Language:
English
Keywords:
Pubs id:
1182231
Local pid:
pubs:1182231
Deposit date:
2021-08-07

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