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Classification of Artistic Styles Using Binarized Features Derived from a Deep Neural Network
[chapter]
2015
Lecture Notes in Computer Science
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With the vast expansion of digital contemporary painting collections, automatic theme stylization has grown in demand in both academic and commercial fields. The recent interest in deep neural networks has provided powerful visual features that achieve state-of-the-art results in various visual classification tasks. In this work, we examine the perceptiveness of these features in identifying artistic styles in paintings, and suggest a compact binary representation of the paintings. Combined
doi:10.1007/978-3-319-16178-5_5
fatcat:j7n3guyptjf6vmqrkcwwl6os3u