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VTC: improving video-text retrieval with user comments

Abstract:

Multi-modal retrieval is an important problem for many applications, such as recommendation and search. Current benchmarks and even datasets are often manually constructed and consist of mostly clean samples where all modalities are well-correlated with the content. Thus, current video-text retrieval literature largely focuses on video titles or audio transcripts, while ignoring user comments, since users often tend to discuss topics only vaguely related to the video. Despite the ubiquity of ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-031-19833-5_36

Authors


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Role:
Author
ORCID:
0000-0002-3423-9373
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Role:
Author
ORCID:
0000-0001-8410-2570
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Role:
Author
ORCID:
0000-0002-8533-4020
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0003-3994-8045
Publisher:
Springer
Series:
Lecture Notes in Computer Science
Volume:
13695
Pages:
616-633
Publication date:
2022-11-04
Event title:
17th European Conference on Computer Vision (ECCV 2022)
Event location:
Tel Aviv, Israel
Event website:
https://eccv2022.ecva.net/
Event start date:
2022-10-23
Event end date:
2022-10-27
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
EISBN:
9783031198335
ISBN:
9783031198328
Language:
English
Keywords:
Pubs id:
1318516
Local pid:
pubs:1318516
Deposit date:
2023-02-02

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