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Improving Video Retrieval Using Multilingual Knowledge Transfer

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Advances in Information Retrieval (ECIR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13980))

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Abstract

Video retrieval has seen tremendous progress with the development of vision-language models. However, further improving these models require additional labelled data which is a huge manual effort. In this paper, we propose a framework MKTVR, that utilizes knowledge transfer from a multilingual model to boost the performance of video retrieval. We first use state-of-the-art machine translation models to construct pseudo ground-truth multilingual video-text pairs. We then use this data to learn a video-text representation where English and non-English text queries are represented in a common embedding space based on pretrained multilingual models. We evaluate our proposed approach on four English video retrieval datasets such as MSRVTT, MSVD, DiDeMo and Charades. Experimental results demonstrate that our approach achieves state-of-the-art results on all datasets outperforming previous models. Finally, we also evaluate our model on a multilingual video-retrieval dataset encompassing six languages and show that our model outperforms previous multilingual video retrieval models in a zero-shot setting.

A. Madasu—Contribution during Avinash’s internship at Intel.

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Notes

  1. 1.

    https://github.com/FreddeFrallan/Multilingual-CLIP.

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Author information

Authors and Affiliations

  1. Cognitive Computing Research, Intel Labs, Santa Clara, USA

    Avinash Madasu, Estelle Aflalo, Gabriela Ben Melech Stan, Shao-Yen Tseng & Vasudev Lal

  2. University of North Carolina at Chapel Hill, Chapel Hill, USA

    Avinash Madasu & Gedas Bertasius

Authors
  1. Avinash Madasu
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  2. Estelle Aflalo
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  3. Gabriela Ben Melech Stan
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  4. Shao-Yen Tseng
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  5. Gedas Bertasius
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  6. Vasudev Lal
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Corresponding author

Correspondence to Vasudev Lal .

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    Jaap Kamps

  2. Université Grenoble-Alpes, Saint-Martin-d’Hères, France

    Lorraine Goeuriot

  3. Università della Svizzera Italiana, Lugano, Switzerland

    Fabio Crestani

  4. University of Copenhagen, Copenhagen, Denmark

    Maria Maistro

  5. University of Tsukuba, Ibaraki, Japan

    Hideo Joho

  6. Dublin City University, Dublin, Ireland

    Brian Davis

  7. Dublin City University, Dublin, Ireland

    Cathal Gurrin

  8. Universität Regensburg, Regensburg, Germany

    Udo Kruschwitz

  9. Dublin City University, Dublin, Ireland

    Annalina Caputo

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Madasu, A., Aflalo, E., Ben Melech Stan, G., Tseng, SY., Bertasius, G., Lal, V. (2023). Improving Video Retrieval Using Multilingual Knowledge Transfer. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13980. Springer, Cham. https://doi.org/10.1007/978-3-031-28244-7_42

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  • DOI: https://doi.org/10.1007/978-3-031-28244-7_42

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