{"title":"基于海报图像的深度神经网络电影类型分类","authors":"W. Chu, Hung-Jui Guo","doi":"10.1145/3132515.3132516","DOIUrl":null,"url":null,"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.","PeriodicalId":395519,"journal":{"name":"Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"Movie Genre Classification based on Poster Images with Deep Neural Networks\",\"authors\":\"W. Chu, Hung-Jui Guo\",\"doi\":\"10.1145/3132515.3132516\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":395519,\"journal\":{\"name\":\"Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3132515.3132516\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3132515.3132516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Movie Genre Classification based on Poster Images with Deep Neural Networks
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.