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Frozen in time: A joint video and image encoder for end-to-end retrieval

Abstract:

Our objective in this work is video-text retrieval – in particular a joint embedding that enables efficient text-to-video retrieval. The challenges in this area include the design of the visual architecture and the nature of the training data, in that the available large scale video-text training datasets, such as HowTo100M, are noisy and hence competitive performance is achieved only at scale through large amounts of compute.We address both these challenges in this paper. We propose an end-t...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ICCV48922.2021.00175

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573
Publisher:
IEEE
Host title:
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Pages:
1708-1718
Publication date:
2022-02-28
Acceptance date:
2021-07-23
Event title:
2021 International Conference on Computer Vision (ICCV 2021)
Event location:
Virtual Event
Event website:
https://iccv2021.thecvf.com/home
Event start date:
2021-10-11
Event end date:
2021-10-17
DOI:
EISSN:
2380-7504
EISBN:
978-1-6654-2812-5
ISBN:
978-1-6654-2813-2
Language:
English
Keywords:
Pubs id:
1233022
Local pid:
pubs:1233022
Deposit date:
2022-01-19

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