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Long-term tracking in the wild: a benchmark

Abstract:

We introduce the OxUvA dataset and benchmark for evaluating single-object tracking algorithms. Benchmarks have enabled great strides in the field of object tracking by defining standardized evaluations on large sets of diverse videos. However, these works have focused exclusively on sequences that are just tens of seconds in length and in which the target is always visible. Consequently, most researchers have designed methods tailored to this “short-term” scenario, which is poorly representat...

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

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Publisher copy:
10.1007/978-3-030-01219-9_41

Authors


Valmadre, J 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
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
New College
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Publisher:
Springer, Cham Publisher's website
Volume:
11207
Pages:
692-707
Series:
Lecture Notes in Computer Science
Publication date:
2018-10-07
Acceptance date:
2018-07-03
DOI:
ISSN:
0302-9743
Pubs id:
pubs:940498
URN:
uri:23a10a1c-a4dd-405a-bf9c-b7838b15c9f8
UUID:
uuid:23a10a1c-a4dd-405a-bf9c-b7838b15c9f8
Local pid:
pubs:940498
ISBN:
9783030012182

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