Outline of object recognition

Results: 84



#Item
61What, Where and Who? Telling the Story of an Image by Activity Classification, Scene Recognition and Object Categorization Li Fei-Fei and Li-Jia Li  Abstract We live in a richly visual world. More than one third of the

What, Where and Who? Telling the Story of an Image by Activity Classification, Scene Recognition and Object Categorization Li Fei-Fei and Li-Jia Li Abstract We live in a richly visual world. More than one third of the

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Source URL: vision.stanford.edu

Language: English
62Journal of Experimental Psychology: General 2016, Vol. 145, No. 1, 82–94 © 2016 American Psychological Association/$12.00 http://dx.doi.orgxge0000129

Journal of Experimental Psychology: General 2016, Vol. 145, No. 1, 82–94 © 2016 American Psychological Association/$12.00 http://dx.doi.orgxge0000129

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Source URL: vision.stanford.edu

Language: English - Date: 2016-01-05 19:05:51
63Objects as Attributes for Scene Classification Li-Jia Li*, Hao Su*, Yongwhan Lim, Li Fei-Fei Computer Science Department, Stanford University Abstract. Robust low-level image features have proven to be effective represen

Objects as Attributes for Scene Classification Li-Jia Li*, Hao Su*, Yongwhan Lim, Li Fei-Fei Computer Science Department, Stanford University Abstract. Robust low-level image features have proven to be effective represen

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Source URL: vision.stanford.edu

Language: English - Date: 2010-07-14 19:17:56
64Automatic Thumbnail Generation Based on Visual Representativeness and Foreground Recognizability Jingwei Huang1,2,⋆ , Huarong Chen1,2,⋆ , Bin Wang1,2 , Stephen Lin3 1  School of Software, Tsinghua University 2 Tsingh

Automatic Thumbnail Generation Based on Visual Representativeness and Foreground Recognizability Jingwei Huang1,2,⋆ , Huarong Chen1,2,⋆ , Bin Wang1,2 , Stephen Lin3 1 School of Software, Tsinghua University 2 Tsingh

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Source URL: www.cv-foundation.org

Language: English - Date: 2015-10-24 14:57:22
65Local Convolutional Features with Unsupervised Training for Image Retrieval Mattis Paulin 1 Julien Mairal1 1  Inria ∗

Local Convolutional Features with Unsupervised Training for Image Retrieval Mattis Paulin 1 Julien Mairal1 1 Inria ∗

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Source URL: www.cv-foundation.org

Language: English - Date: 2015-10-24 14:55:25
66CGI2012 manuscript No. (will be inserted by the editor) Transferring Characteristic Proportions to Modify the Artistic Style of Cartoons Philip Buchanan · Michael Doggett

CGI2012 manuscript No. (will be inserted by the editor) Transferring Characteristic Proportions to Modify the Artistic Style of Cartoons Philip Buchanan · Michael Doggett

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Source URL: fileadmin.cs.lth.se

Language: English - Date: 2012-03-30 08:16:12
67Human Action Recognition by Learning Bases of Action Attributes and Parts Bangpeng Yao1 , Xiaoye Jiang2 , Aditya Khosla1 , Andy Lai Lin3 , Leonidas Guibas1 , and Li Fei-Fei1 1 2

Human Action Recognition by Learning Bases of Action Attributes and Parts Bangpeng Yao1 , Xiaoye Jiang2 , Aditya Khosla1 , Andy Lai Lin3 , Leonidas Guibas1 , and Li Fei-Fei1 1 2

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Source URL: geometry.stanford.edu

Language: English - Date: 2011-09-28 17:56:07
68IEEE TRANSACTIONS OF PATTERN ANALYSIS AND MACHINE INTELLIGENCE  1 Multi-Scale Categorical Object Recognition Using Contour Fragments

IEEE TRANSACTIONS OF PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1 Multi-Scale Categorical Object Recognition Using Contour Fragments

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Source URL: jamie.shotton.org

Language: English - Date: 2013-04-10 20:20:44
69Fine-Grained Recognition without Part Annotations Jonathan Krause1 Hailin Jin2 1 Stanford University

Fine-Grained Recognition without Part Annotations Jonathan Krause1 Hailin Jin2 1 Stanford University

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Source URL: vision.stanford.edu

Language: English - Date: 2015-07-12 18:35:39
70M  Machine Recognition of Objects Tomaso Poggio and Shimon Ullman Department of Brain and Cognitive Sciences, McGovern Institute, Massachusetts Institute of

M Machine Recognition of Objects Tomaso Poggio and Shimon Ullman Department of Brain and Cognitive Sciences, McGovern Institute, Massachusetts Institute of

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Source URL: www.cse.cuhk.edu.hk

Language: English - Date: 2015-04-11 07:17:47