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MM-AU:Towards Multimodal Understanding of Advertisement Videos

Authors:

Krishna Somandepalli,

Shrikanth NarayananAuthors Info & Claims

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

Pages 86 - 95

https://doi.org/10.1145/3581783.3612371

Published: 27 October 2023 Publication History

Abstract

Advertisement videos (ads) play an integral part in the domain of Internet e-commerce, as they amplify the reach of particular products to a broad audience or can serve as a medium to raise awareness about specific issues through concise narrative structures. The narrative structures of advertisements involve several elements like reasoning about the broad content (topic and the underlying message) and examining fine-grained details involving the transition of perceived tone due to the sequence of events and interaction among characters. In this work, to facilitate the understanding of advertisements along the three dimensions of topic categorization, perceived tone transition, and social message detection, we introduce a multimodal multilingual benchmark called MM-AU comprised of 8.4 K videos (147hrs) curated from multiple web-based sources. We explore multiple zero-shot reasoning baselines through the application of large language models on the ads transcripts. Further, we demonstrate that leveraging signals from multiple modalities, including audio, video, and text, in multimodal transformer-based supervised models leads to improved performance compared to unimodal approaches.

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Cited By

Song QJia ZJia WZhao WHu MLiu C(2024)News-MESI: A Dataset for Multimodal News Excerpt Segmentation and IdentificationIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2024.33698668:4(3001-3016)Online publication date: Aug-2024
https://doi.org/10.1109/TETCI.2024.3369866
Giannakopoulos NReklitis DTerzi MSakas DKanellos N(2024)Video marketing for decentralized finance platforms’ servicesJournal of Financial Services Marketing10.1057/s41264-024-00288-229:4(1225-1259)Online publication date: 15-Oct-2024
https://doi.org/10.1057/s41264-024-00288-2

Index Terms

MM-AU:Towards Multimodal Understanding of Advertisement Videos

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cover image ACM Conferences

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

October 2023

9913 pages

ISBN:9798400701085

DOI:10.1145/3581783

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada & MBZUAI, UAE
,
Tao Mei
HiDream.ai, China
,
Rita Cucchiara
University of Modena and Reggio Emilia, Italy
,
Program Chairs:
Marco Bertini
University of Florence, Italy
,
Diana Patricia Tobon Vallejo
Unversidad de Medellin, Colombia
,
Pradeep K. Atrey
University at Albany, State University of New York, USA
,
M. Shamim Hossain
M. Shamim Hossain (King Saud University, KSA

Copyright © 2023 Owner/Author.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

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Published: 27 October 2023

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MM '23: The 31st ACM International Conference on Multimedia

October 29 - November 3, 2023

Ottawa ON, Canada

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Cited By

Song QJia ZJia WZhao WHu MLiu C(2024)News-MESI: A Dataset for Multimodal News Excerpt Segmentation and IdentificationIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2024.33698668:4(3001-3016)Online publication date: Aug-2024
https://doi.org/10.1109/TETCI.2024.3369866
Giannakopoulos NReklitis DTerzi MSakas DKanellos N(2024)Video marketing for decentralized finance platforms’ servicesJournal of Financial Services Marketing10.1057/s41264-024-00288-229:4(1225-1259)Online publication date: 15-Oct-2024
https://doi.org/10.1057/s41264-024-00288-2

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