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Movie genre classification based on poster images with deep neural networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose to achieve movie genre classification based only on movie poster images. A deep neural network is constructed to jointly describe visual appearance and object information, and classify a given movie poster image into genres. Because a movie may belong to multiple genres, this is a multi-label image classification problem. To facilitate related studies, we collect a large-scale movie poster dataset, associated with various metadata. Based on this dataset, we fine-tune a pretrained convolutional neural network to extract visual representation, and adopt a state-of-the-art framework to detect objects in posters. Two types of information is then integrated by the proposed neural network. In the evaluation, we show that the proposed method yields encouraging performance, which is much better than previous works.

Original languageEnglish
Title of host publicationMUSA2 2017 - Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, co-located with MM 2017
PublisherAssociation for Computing Machinery, Inc
Pages39-45
Number of pages7
ISBN (Electronic)9781450355094
DOIs
Publication statusPublished - 2017 Oct 27
Event1st ACM MM Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, MUSA2 2017 - Mountain View, United States
Duration: 2017 Oct 27 → …

Publication series

NameMUSA2 2017 - Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, co-located with MM 2017

Conference

Conference1st ACM MM Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, MUSA2 2017
Country/TerritoryUnited States
CityMountain View
Period17-10-27 → …

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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