Movie Genre Classification based on Poster Images with Deep Neural Networks

Wei-Ta Chu and Hung-Jui Guo

Multimedia Computing Laboratory
Dept. of Computer Science and Information Engineering
National Chung Cheng University

1. Introduction

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.

2. Movie Poster Dataset

This dataset was collected from the IMDB website. One poster image was collected from one (mostly) Hollywood movie released from 1980 to 2015. Each poster image is associated with a movie as well as some metadata like ID, genres, and box office. The ID of each image is set as its file name.

3. Citation

Please cite our work if you utilize this dataset.

Wei-Ta Chu and Hung-Jui Guo, ˇ§Movie Genre Classification based on Poster Images with Deep Neural Networks,ˇ¨ Proceedings of International Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, pp. 39-45, 2017. (in conjunction with ACM Multimedia 2017)


Any problem please contact .

[Main Page]

Last Updated: November 1, 2017