Movie Genre Classification based on Poster Images with Deep Neural Networks

W. Chu, Hung-Jui Guo
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引用次数: 53

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.
基于海报图像的深度神经网络电影类型分类
我们建议仅基于电影海报图像来实现电影类型分类。构建深度神经网络,共同描述视觉外观和对象信息,并对给定的电影海报图像进行类型分类。因为一部电影可能属于多个类型,所以这是一个多标签图像分类问题。为了便于相关研究,我们收集了一个大规模的电影海报数据集,并与各种元数据相关联。基于此数据集,我们对预训练的卷积神经网络进行微调以提取视觉表示,并采用最先进的框架来检测海报中的物体。两种类型的信息然后被所提出的神经网络整合。在评估中,我们表明所提出的方法产生了令人鼓舞的性能,比以往的工作要好得多。
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