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abstract

AI4TV 2020: 2nd International Workshop on AI for Smart TV Content Production, Access and Delivery

Published: 12 October 2020 Publication History

Abstract

Technological developments in comprehensive video understanding - detecting and identifying visual elements of a scene, combined with audio understanding (music, speech), as well as aligned with textual information such as captions, subtitles, etc. and background knowledge - have been undergoing a significant revolution during recent years. The workshop brings together experts from academia and industry in order to discuss the latest progress in artificial intelligence research in topics related to multimodal information analysis, and in particular, semantic analysis of video, audio, and textual information for smart digital TV content production, access and delivery.

References

[1]
Vishal Kaushal, Suraj Kothawade, Rishabh Iyer, and Ganesh Ramakrishnan. 2020. Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework. In Proc. Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV 2020) at ACM Multimedia 2020. ACM, Seattle, WA, USA.
[2]
Lyndon Nixon. 2020. Predicting your future audience's popular topics to optimize TV content marketing success. In Proc. Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV 2020) at ACM Multimedia 2020. ACM, Seattle, WA, USA.
[3]
Dejan Porjazovski, Juho Leinonen, and Mikko Kurimo. 2020. Named Entity Recognition for Spoken Finnish. In Proc. Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV 2020) at ACM Multimedia 2020. ACM, Seattle, WA, USA.
[4]
Yashaswi Rauthan, Vatsala Singh, Rishabh Agrawal, Satej Kadlay, Niranjan Pedanekar, Shirish Karande, Iaphi Tariang, and Manasi Malik. 2020. Avoid Crowding in the Battlefield: Semantic Placement of Social Messages in Entertainment Programs. In Proc. Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV 2020) at ACM Multimedia 2020. ACM, Seattle, WA, USA.
[5]
Syeda Maryam Fatima Taqvi, Marina Shehzad, and Sami Murtaza. 2020. Neural Style Transfer Based Voice Mimicking for Personalized Audio Stories. In Proc. Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV 2020) at ACM Multimedia 2020. ACM, Seattle, WA, USA.
[6]
Raphaël Troncy, Jorma Laaksonen, Hamed Tavakoli, Lyndon Nixon, and Vasileios Mezaris. 2019. AI4TV 2019: 1st International Workshop on AI for Smart TV Content Production, Access and Delivery. In Proc. ACM Multimedia 2019. ACM, Nice, France.
[7]
Miggi Zwicklbauer, Willy Lamm, Martin Gordon, Konstantinos Apostolidis, Basil Philipp, and Vasileios Mezaris. 2020. Video Analysis for Interactive Story Creation: The Sandmännchen Showcase. In Proc. Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV 2020) at ACM Multimedia 2020. ACM, Seattle, WA, USA.

Cited By

View all
  • (2024)AI and data-driven media analysis of TV content for optimised digital content marketingMultimedia Systems10.1007/s00530-023-01195-730:1Online publication date: 19-Jan-2024
  • (2021)Content Wizard: demo of a trans-vector digital video publication toolProceedings of the 2021 ACM International Conference on Interactive Media Experiences10.1145/3452918.3468083(296-298)Online publication date: 21-Jun-2021

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Published In

cover image ACM Conferences
MM '20: Proceedings of the 28th ACM International Conference on Multimedia
October 2020
4889 pages
ISBN:9781450379885
DOI:10.1145/3394171
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 October 2020

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Author Tags

  1. artificial intelligence
  2. intelligent multimedia
  3. tv content analysis
  4. tv content annotation
  5. tv content delivery
  6. tv content production

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  • EU Horizon 2020

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MM '20
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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all
  • (2024)AI and data-driven media analysis of TV content for optimised digital content marketingMultimedia Systems10.1007/s00530-023-01195-730:1Online publication date: 19-Jan-2024
  • (2021)Content Wizard: demo of a trans-vector digital video publication toolProceedings of the 2021 ACM International Conference on Interactive Media Experiences10.1145/3452918.3468083(296-298)Online publication date: 21-Jun-2021

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