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Hierarchical attentive recurrent tracking

Abstract:

Class-agnostic object tracking is particularly difficult in cluttered environments as target specific discriminative models cannot be learned a priori. Inspired by how the human visual cortex employs spatial attention and separate “where” and “what” processing pathways to actively suppress irrelevant visual features, this work develops a hierarchical attentive recurrent model for single object tracking in videos. The first layer of attention discards the majority of background by selecting a ...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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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
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
Pembroke College
Publisher:
Neural Information Processing Systems Publisher's website
Publication date:
2018-07-01
Acceptance date:
2017-09-04
Pubs id:
pubs:820389
URN:
uri:8fa0fddd-7b5f-4903-b40d-9b4133a3965d
UUID:
uuid:8fa0fddd-7b5f-4903-b40d-9b4133a3965d
Local pid:
pubs:820389

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