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5 CNN( ) CNN( ) CNN(3 ) 6. CNN,,,,. [4] CNN,,,, miamaterial,,, 5,,,,, 4 8, 5 CNN,.% 6.95% CNN,,,,, 4, 5, 5 8,,,,,., 6,,,,, CNN, 5,,, Interiror Nature, CNN 95, 8,,, CNN,,,.,, CNN,,,, [9],, 5., CNN, CNN,,, CNN, CNN,, Motoyoshi,,, Motoyoshi,, [], CNN,, [] T. Abe, T. Okatani, and K. Deguchi. Recognizing surface qualities from natural images based on learning to rank. In Proc. ICPR, pages , 0. [] B. L. Anderson and J. Kim. Image statistics do not explain the perception of gloss and lightness. journal of Vision, 9(), 009. [3] Y. Bengio, A. C. Courville, and P. Vincent. Unsuper- c 03 Information Processing Society of Japan 5
6 (Interior/Nature) 8 CNN 3.,,, (Interior/Nature). vised feature learning and deep learning: A review and new perspectives. CoRR, abs/ , 0. [4] D. C. Ciresan, U. Meier, and J. Schmidhuber. Multicolumn deep neural networks for image classification. In Proc. CVPR, 0. [5] M. Crosier and L. D. Griffin. Using basic image features for texture classification. International Journal of Computer Vision, 88(3): , 00. [6] R. O. Dror, E. H. Adelson, and A. S. Willsky. Recognition of surface reflectance properties from a single image under unknown real-world illumination. In Proc. the Workshop on Identifying Objects Across Variations in Lighting at CVPR, 00. [7] C. Hiramatsu, N. Goda, and H. Komatsu. Transformation from image-based to perceptual representation of materials along the human ventral visual pathway. NeuroImage, 57():48-494, 0. [8] D. Hu, L. Bo, and X. Ren. Toward robust material recognition for everyday objects. In Proc. BMVC, pages , 0. [9] A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 0. [0] C. Liu, L. Sharan, E. H. Adelson, and R. Rosenholtz. Exploring features in a bayesian framework for material recognition. In Proc. CVPR, 00. [] S. Lombardi and K. Nishino. Reflectance and natural illumination from a single image. In Proc. ECCV, 0. [] I. Motoyoshi. Highlight shading relationship as a cue for the perception of translucent and transparent materials. Journal of Vision, 0(9), 00. [3] I. Motoyoshi, S. Nishida, L. Sharan, and E. H. Adelson. Image statistics and the perception of surface qualities. Nature, 447(74):06-09, 007. [4] B. A. Olshausen and D. J. Field. Emergence of simplecell receptive field properties by learning a sparse code for natural images. Nature, 38(6583): , 996. [5] D. Parikh and K. Grauman. Relative attributes. In Proc. ICCV, 0. [6] F. Romeiro and T. Zickler. Blind reflectrometry. In Proc. ECCV, 00. [7] R. Timofte and L. Van Gool. A training-free classification framework for textures, writers,and materials. In Proc. BMVC, pages , 0. c 03 Information Processing Society of Japan 6
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The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). The material has been made available on the website
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