It is our great pleasure to welcome you to the 2020 International Workshop on AI for Smart TV Content Production, Access and Delivery - AI4TV 2020. New scientific breakthroughs in video understanding through the application of AI techniques along with the increase in the volume of multimedia content and more computational power have led to significant improvements in automated video description and have opened fresh avenues for the seamless combination of multiple modalities' analysis. The main goal of the workshop is to promote AI techniques for multimedia analysis to enable smarter content production, access and delivery with the emphasis on large TV and radio program archives.
Proceeding Downloads
AI in the Media Spotlight
The use of AI technology offers many new opportunities for the media sector; in particular, it leads to an increase in productivity and efficiency to convey relevant information to appropriate viewers quickly and accurately.
In this keynote, I will ...
And, Action! Towards Leveraging Multimodal Patterns for Storytelling and Content Analysis
Humans perform intelligent tasks by productively leveraging relevant information from numerous sensory and experiential inputs, and recent scientific and hardware advances have made it increasingly possible for machines to attempt this as well. However, ...
Predicting Your Future Audience's Popular Topics to Optimize TV Content Marketing Success
TV broadcasters and other organizations with online media collections which wish to extend the reach of and engagement with their media assets conduct digital marketing activities. The marketing success depends on the relevance of the topics of the ...
Neural Style Transfer Based Voice Mimicking for Personalized Audio Stories
This paper demonstrates a CNN based neural style transfer on audio dataset to make storytelling a personalized experience by asking users to record a few sentences that are used to mimic their voice. User audios are converted to spectrograms, the style ...
Video Analysis for Interactive Story Creation: The Sandmännchen Showcase
This paper presents a method to interactively create a new Sandmannchen story. We built an application which is deployed on a smart speaker, interacts with a user, selects appropriate segments from a database of Sandmannchen episodes and combines them ...
Named Entity Recognition for Spoken Finnish
In this paper we present a Bidirectional LSTM neural network with a Conditional Random Field layer on top, which utilizes word, character and morph embeddings in order to perform named entity recognition on various Finnish datasets. To overcome the lack ...
Avoid Crowding in the Battlefield: Semantic Placement of Social Messages in Entertainment Programs
- Yashaswi Rauthan,
- Vatsala Singh,
- Rishabh Agrawal,
- Satej Kadlay,
- Niranjan Pedanekar,
- Shirish Karande,
- Manasi Malik,
- Iaphi Tariang
Crisis situations often require authorities to convey important messages to a large population of varying demographics. An example of such a message is maintain a distance of 6 ft from others in times of the present COVID-19 crisis. In this paper, we ...
Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework
Automatic video summarization is still an unsolved problem due to several challenges. We take steps towards making it more realistic by addressing the following challenges. Firstly, the currently available datasets either have very short videos or have ...
- Proceedings of the 2nd International Workshop on AI for Smart TV Content Production, Access and Delivery