論文- 岡谷 貴之 -
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件数:93件
[2017]
1.Truncating Wide Networks using Binary Tree Architectures.[Proceedings of International Conference on Computer Vision (ICCV),(2017)]Y. Zhang, M. Ozay, S. Li, T. Okatani
2.Self-calibration-based Approach to Critical Motion Sequences of Rolling-shutter Structure from Motion.[Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR),(2017)]Eisuke Ito, Takayuki Okatani
3.Learning to describe E-commerce images from noisy online data.[Proceedings of Asian Conference on Computer Vision (ACCV) / Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),10115 LNCS,(2017),85-100]Yashima, T. and Okazaki, N. and Inui, K. and Yamaguchi, K. and Okatani, T.
10.1007/978-3-319-54193-8_6
http://www.scopus.com/inward/record.url?eid=2-s2.0-85016296170&partnerID=40
4.Temporal city modeling using street level imagery.[Computer Vision and Image Understanding,157,(2017),55-71]Sakurada, K. and Tetsuka, D. and Okatani, T.
10.1016/j.cviu.2017.01.012
http://www.scopus.com/inward/record.url?eid=2-s2.0-85012908183&partnerID=40
5.Integrating deep features for material recognition.[Proceedings - International Conference on Pattern Recognition,(2017),7900209-]Zhang, Y. and Ozay, M. and Liu, X. and Okatani, T.
10.1109/ICPR.2016.7900209
http://www.scopus.com/inward/record.url?eid=2-s2.0-85019080123&partnerID=40
6.Attention to describe products with attributes.[Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017,(2017),7986839-]Li, S. and Yamaguchi, K. and Okatani, T.
10.23919/MVA.2017.7986839
http://www.scopus.com/inward/record.url?eid=2-s2.0-85027838470&partnerID=40
[2016]
7.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
8.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
9.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
10.Recognizing open-vocabulary relations between objects in images.[Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation, PACLIC 2016,(2016),239-248]Muraoka, M. and Maharjan, S. and Saito, M. and Yamaguchi, K. and Okazaki, N. and Okatani, T. and Inui, K.
http://www.scopus.com/inward/record.url?eid=2-s2.0-85015939069&partnerID=40
11.Automatic attribute discovery with neural activations.[Proceedings of European Conference on Computer Vision (ECCV) / Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),9908 LNCS,(2016),252-268]Vittayakorn, S. and Umeda, T. and Murasaki, K. and Sudo, K. and Okatani, T. and Yamaguchi, K.
10.1007/978-3-319-46493-0_16
http://www.scopus.com/inward/record.url?eid=2-s2.0-84990055167&partnerID=40
12.Design of kernels in convolutional neural networks for image classification.[Proceedings of European Conference on Computer Vision (ECCV) / Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),9911 LNCS,(2016),51-66]Sun, Z. and Ozay, M. and Okatani, T.
10.1007/978-3-319-46478-7_4
http://www.scopus.com/inward/record.url?eid=2-s2.0-84990041427&partnerID=40
[2015]
13.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
14.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
15.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
16.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
17.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
18.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
[2014]
19.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]
20.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
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