論文- 岡谷 貴之 -
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件数:87件
[2016]
1.Learning to Describe E-Commerce Images from Noisy Online Data.[In Proceedings of Asian Conference on Computer Vision,(2016)]Yashima, T., Okazaki, N., Inui, K., Yamaguchi, K., Okatani, T.
2.Automatic Attribute Discovery with Neural Activations.[In Proceedings of European Conference on Computer Vision,(2016),252-268]Sirion Vittayakorn, Takayuki Umeda, Kazuhiko Murasaki, Kyoko Sudo, Takayuki Okatani, Kota Yamaguchi
3.Design of Kernels in Convolutional Neural Networks for Image Classification.[Proceedings of European Conference on Computer Vision,(2016),51-66]Zhun Sun, Mete Ozay, Takayuki Okatani
4.A gaze-reactive display for simulating depth-of-field of eyes when viewing scenes with multiple depths.[IEICE Trans Inf Syst,E99D(3),(2016),739-746]Orikasa, T b and Okatani, T.a
10.1587/transinf.2015EDP7110
http://www.scopus.com/inward/record.url?eid=2-s2.0-84959545082&partnerID=40
5.Hybrid macro-micro visual analysis for city-scale state estimation.[Comput Vision Image Understanding,146,(2016),86-98]Sakurada, K.a and Okatani, T.a and Kitani, K.M
10.1016/j.cviu.2016.02.017
http://www.scopus.com/inward/record.url?eid=2-s2.0-84961564370&partnerID=40
6.Separation of reflection components by sparse non-negative matrix factorization.[Comput Vision Image Understanding,146,(2016),77-85]Akashi, Y.a and Okatani, T
10.1016/j.cviu.2015.09.001
http://www.scopus.com/inward/record.url?eid=2-s2.0-84962420705&partnerID=40
[2015]
7.Massive city-scale surface condition analysis using ground and aerial imagery.[Lect. Notes Comput. Sci.,9003,(2015),49-64]Sakurada, K.a and Okatani, T.a and Kitani, K.M
10.1007/978-3-319-16865-4_4
http://www.scopus.com/inward/record.url?eid=2-s2.0-84938870905&partnerID=40
8.Possibility to use product image and review text based on the association between onomatopoeia and texture.[Trans. Jpn. Soc. Artif. Intell.,30(1),(2015),124-137]Doizaki, R and Iiba, S.a and Okatani, T.b and Sakamoto, M.a
http://www.scopus.com/inward/record.url?eid=2-s2.0-84920497822&partnerID=40
9.Understanding convolutional neural networks in terms of category-level attributes.[Lect. Notes Comput. Sci.,9004,(2015),362-375]Ozeki, M. and Okatani, T.
10.1007/978-3-319-16808-1_25
http://www.scopus.com/inward/record.url?eid=2-s2.0-84945972026&partnerID=40
10.Separation of Reflection Components by Sparse Non-Negative Matrix Factorization.[Lect. Notes Comput. Sci.,9007,(2015),611-625]Akashi, Y. and Okatani, T.
10.1007/978-3-319-16814-2_40
http://www.scopus.com/inward/record.url?eid=2-s2.0-84929629176&partnerID=40
11.Detecting building-level changes of a city using street images and a 2D city map.[Proc. - IEEE Winter Conf. Appl. Comput. Vis., WACV,(2015),7045907-]Tetsuka, D. and Okatani, T.
10.1109/WACV.2015.53
http://www.scopus.com/inward/record.url?eid=2-s2.0-84925433190&partnerID=40
12.Transformation of Markov Random Fields for marginal distribution estimation.[Proc IEEE Comput Soc Conf Comput Vision Pattern Recognit,07-12-June-2015,(2015),7298680-]Saito, M. and Okatani, T.
10.1109/CVPR.2015.7298680
http://www.scopus.com/inward/record.url?eid=2-s2.0-84959220500&partnerID=40
[2014]
13.Creating multi-viewpoint panoramas of streets with sparsely located buildings.[Springer Tracts Adv. Rob.,92,(2014),65-79]Okatani, T. and Yanagisawa, J. and Tetsuka, D. and Sakurada, K. and Deguchi, K.
10.1007/978-3-642-40686-7_5
http://www.scopus.com/inward/record.url?eid=2-s2.0-84897694378&partnerID=40
[2013]
14.Discrete Maximum Posterior Marginal Inference for Non-uniformly Discretized Variable Space.[Proceedings of Computer Vision and Pattern Recognition,(2013)]Masaki Saito, Takayuki Okatani,Koichiro Deguchi
15.Detecting Changes in 3D Structure of a Scene from Multi-view Images Captured by a Vehicle-mounted Camera.[Proceedings of Computer Vision and Pattern Recognition,(2013)]Ken Sakurada, Takayuki Okatani,Koichiro Deguchi
16.Discrete MRF inference of marginal densities for non-uniformly discretized variable space.[Proc IEEE Comput Soc Conf Comput Vision Pattern Recognit,(2013),6618859-]Saito, M. and Okatani, T. and Deguchi, K.
10.1109/CVPR.2013.15
http://www.scopus.com/inward/record.url?eid=2-s2.0-84887373213&partnerID=40
17.Improving accuracy of planar tracking by resolving resolution inconsistencies.[IPSJ Trans. Comput. Vis. Appl.,5,(2013),109-113]Ushiki, T. and Ito, E. and Okatani, T.
10.2197/ipsjtcva.5.109
http://www.scopus.com/inward/record.url?eid=2-s2.0-84881493625&partnerID=40
18.Detecting changes in 3D structure of a scene from multi-view images captured by a vehicle-mounted camera.[Proc IEEE Comput Soc Conf Comput Vision Pattern Recognit,(2013),6618869-]Sakurada, K. and Okatani, T. and Deguchi, K.
10.1109/CVPR.2013.25
http://www.scopus.com/inward/record.url?eid=2-s2.0-84887399467&partnerID=40
[2012]
19.Recognizing Surface Qualities from Natural Images Based on Learning to Rank.[Proceedings of International Conference on Pattern Recognition,(2012),3712-3715]Takashi Abe, Takayuki Okatani, Koichiro Deguchi
20.Application of the mean field methods to MRF optimization in computer vision.[Proceedings of Computer Vision and Pattern Recognition,(2012),1680-1687]Masaki Saito, Takayuki Okatani, Koichiro Deguchi
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