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We propose a multi-scale multi-channel deep neural network framework that, for the first time, yields sketch recognition performance surpassing that of humans.
Theory of communication. part 1: The analysis of information
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D. Chen, X. Cao, L. Wang, F. Wen, and J. Sun · 2012
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M. Eitz, J. Hays, and M. Alexa · 2012
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A performance evaluation of gradient field hog descriptor for sketch based image retrieval
R. Hu and J. Collomosse · 2013
Return of the devil in the details: Delving deep into convolutional nets
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
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Cross-modal face matching: beyong viewed sketches
S. Ouyang, T. Hospedales, Y. Song, and X. Li · 2014
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R. G. Schneider and T. Tuytelaars · 2014
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F. Yin, Q. Wang, X. Zhang, and C. Liu · 2013
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Free-hand sketch recognition by multi-kernel feature learning
Y. Li, T. M. Hospedales, Y. Song, and S. Gong · 2015
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Very deep convolutional networks for large-scale image recognition
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