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SiamMask: A framework for fast online object tracking and segmentation

Abstract:

In this article, we introduce SiamMask, a framework to perform both visual object tracking and video object segmentation, in real-time, with the same simple method. We improve the offline training procedure of popular fully-convolutional Siamese approaches by augmenting their losses with a binary segmentation task. Once the offline training is completed, SiamMask only requires a single bounding box for initialization and can simultaneously carry out visual object tracking and segmentation at ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TPAMI.2022.3172932

Authors


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Role:
Author
ORCID:
0000-0001-9237-8825
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Role:
Author
ORCID:
0000-0003-1031-5420
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Transactions on Pattern Analysis and Machine Intelligence More from this journal
Volume:
45
Issue:
3
Pages:
3072-3089
Publication date:
2023-02-03
Acceptance date:
2022-03-01
DOI:
EISSN:
1939-3539
ISSN:
0162-8828
Language:
English
Keywords:
Pubs id:
1331629
Local pid:
pubs:1331629
Deposit date:
2023-03-30

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