Citation

See, John Su Yang and Wong, Lai Kuan and Kairanbay, Magzhan (2019) Paying Attention to Style: Recognizing Photo Styles with Convolutional Attentional Units. In: Computer Vision – ACCV 2018 Workshops. Paying Attention to Style: Recognizing Photo Styles with Convolutional Attentional Units, 11367 . Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 110-124. ISBN 978-3-030-21074-8

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Abstract

The notion of style in photographs is one that is highly subjective, and often difficult to characterize computationally. Recent advances in learning techniques for visual recognition have encouraged new possibilities for computing aesthetics and other related concepts in images. In this paper, we design an approach for recognizing styles in photographs by introducing adapted deep convolutional neural networks that are attentive towards strong neural activations. The proposed convolutional attentional units act as a filtering mechanism that conserves activations in convolutional blocks in order to contribute more meaningfully towards the visual style classes. State-of-the-art results were achieved on two large image style datasets, demonstrating the effectiveness of our method.

Item Type:	Book Section
Uncontrolled Keywords:	Neural networks
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	23 Sep 2021 02:27
Last Modified:	23 Sep 2021 02:30
URII:	http://shdl.mmu.edu.my/id/eprint/8996

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