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Automatically assigning a group of appropriate semantic tags to one music piece provides an effective way for people to efficiently utilize the massive and ever increasing online and off-line music data. In this paper, we propose a novel end-to-end deep neural network model for automatic music...
In automatic art analysis, models that besides the visual elements of an artwork represent the relationships between the different artistic attributes could be very informative. Those kinds of relationships, however, usually appear in a very subtle way, being extremely difficult to detect with...
The beneficial, complementary nature of visual and textual information to convey information is widely known, for example, in entertainment, news, advertisements, science, or education. While the complex interplay of image and text to form semantic meaning has been thoroughly studied in...
Predicting subjective visual interpretation is important for several prominent tasks in computer vision, including multimedia retrieval. Many approaches reduce this problem to the prediction of adjective or attribute labels from images while neglecting attribute semantics and only processing the...
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