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conference paper

MoZuMa: A Model Zoo for Multimedia Applications

Massonnet, Stephane  
•
Romanelli, Marco  
•
Lebret, Remi  
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January 1, 2022
Proceedings Of The 30Th Acm International Conference On Multimedia, Mm 2022
30th ACM International Conference on Multimedia (MM)

Lots of machine learning models with applications in Multimedia Search are released as Open Source Software. However, integrating these models into an application is not always an easy task due to the lack of a consistent interface to run, train or distribute models. With MoZuMa, we aim at reducing this effort by providing a model zoo for image similarity, text-to-image retrieval, face recognition, object similarity search, video key-frames detection and multilingual text search implemented in a generic interface with a modular architecture. The code is released as Open Source Software at https://github.com/mozuma/mozuma.

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Type
conference paper
DOI
10.1145/3503161.3548542
Web of Science ID

WOS:001150372707075

Author(s)
Massonnet, Stephane  
Romanelli, Marco  
Lebret, Remi  
Poulsen, Niels Jens  
Aberer, Karl  
Corporate authors
ACM
Date Issued

2022-01-01

Publisher

Assoc Computing Machinery

Publisher place

New York

Published in
Proceedings Of The 30Th Acm International Conference On Multimedia, Mm 2022
ISBN of the book

978-1-4503-9203-7

Start page

7335

End page

7338

Subjects

Technology

•

Vision And Language

•

Multimedia Search

•

Open Source Software

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LSIR  
Event nameEvent placeEvent date
30th ACM International Conference on Multimedia (MM)

Lisboa, PORTUGAL

OCT 10-14, 2022

Available on Infoscience
April 3, 2024
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/206775
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