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An empirical study of detection-based video instance segmentation

Abstract:

Video instance segmentation (VIS) is a composite task that requires the joint detection, tracking, and segmentation of objects in a video. In this work, we introduce a complete framework for VIS, which integrates the strengths of instance segmentation and general object tracking in addressing the unique challenges of VIS. In developing the framework, we investigate effective ways of coordinating the two components for maximum benefits while thoroughly investigate their separate contributions....

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
IEEE
Host title:
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Pages:
713-716
Publication date:
2020-03-05
Acceptance date:
2019-09-27
Event title:
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Event location:
Seoul, South Korea
Event website:
https://iccv2019.thecvf.com/
Event start date:
2019-10-27
Event end date:
2019-11-02
DOI:
EISSN:
2473-9944
ISSN:
2473-9936
EISBN:
978-1-7281-5023-9
Language:
English
Keywords:
Pubs id:
1098816
Local pid:
pubs:1098816
Deposit date:
2020-09-09

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