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Deep Architectures for Content Moderation and Movie Content Rating

2022-12-08 19:50:53
Fatih Cagatay Akyon, Alptekin Temizel
arXiv_CV
             
Abstract

Rating a video based on its content is an important step for classifying video age categories. Movie content rating and TV show rating are the two most common rating systems established by professional committees. However, manually reviewing and evaluating scene/film content by a committee is a tedious work and it becomes increasingly difficult with the ever-growing amount of online video content. As such, a desirable solution is to use computer vision based video content analysis techniques to automate the evaluation process. In this paper, related works are summarized for action recognition, multi-modal learning, movie genre classification, and sensitive content detection in the context of content moderation and movie content rating. The project page is available at this https URL}.

Abstract (translated)

URL

https://arxiv.org/abs/2212.04533

PDF

https://arxiv.org/pdf/2212.04533.pdf

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