ADNet: A Deep Network for Detecting Adverts
| Autor: | Hossari, Murhaf, Dev, Soumyabrata, Nicholson, Matthew, McCabe, Killian, Nautiyal, Atul, Conran, Clare, Tang, Jian, Xu, Wei, Pitié, François |
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| Rok vydání: | 2018 |
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| Druh dokumentu: | Working Paper |
| Popis: | Online video advertising gives content providers the ability to deliver compelling content, reach a growing audience, and generate additional revenue from online media. Recently, advertising strategies are designed to look for original advert(s) in a video frame, and replacing them with new adverts. These strategies, popularly known as product placement or embedded marketing, greatly help the marketing agencies to reach out to a wider audience. However, in the existing literature, such detection of candidate frames in a video sequence for the purpose of advert integration, is done manually. In this paper, we propose a deep-learning architecture called ADNet, that automatically detects the presence of advertisements in video frames. Our approach is the first of its kind that automatically detects the presence of adverts in a video frame, and achieves state-of-the-art results on a public dataset. Comment: Published in Proc. 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2018), First two authors contributed equally to this work |
| Databáze: | arXiv |
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