-
1
-
-
37849004888
-
Why we tag: Motivations for annotation in mobile and online media
-
M. Ames and M. Naaman. Why we tag: Motivations for annotation in mobile and online media. In Proc. CHI, 2007.
-
(2007)
Proc. CHI
-
-
Ames, M.1
Naaman, M.2
-
2
-
-
84866726859
-
Understanding and predicting importance in images
-
A. C. Berg, T. L. Berg, H. Daumé III, J. Dodge, A. Goyal, X. Han, A. Mensch, M. Mitchell, A. Sood, K. Stratos, and K. Yamaguchi. Understanding and predicting importance in images. In Proc. CVPR, 2012.
-
(2012)
Proc. CVPR
-
-
Berg, A.C.1
Berg, T.L.2
Daumé, H.3
Dodge, J.4
Goyal, A.5
Han, X.6
Mensch, A.7
Mitchell, M.8
Sood, A.9
Stratos, K.10
Yamaguchi, K.11
-
4
-
-
74049158146
-
NUS-WIDE: A real-world web image database from National University of Singapore
-
T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng. NUS-WIDE: a real-world web image database from National University of Singapore. In Proc. CIVR, 2009.
-
(2009)
Proc. CIVR
-
-
Chua, T.-S.1
Tang, J.2
Hong, R.3
Li, H.4
Luo, Z.5
Zheng, Y.6
-
5
-
-
0038401728
-
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
-
P. Duygulu, K. Barnard, N. D. Freitas, and D. a. Forsyth. Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary. In Proc. ECCV, 2002.
-
(2002)
Proc. ECCV
-
-
Duygulu, P.1
Barnard, K.2
Freitas, N.D.3
Forsyth, D.A.4
-
6
-
-
85083950293
-
Deep convolutional ranking for multilabel image annotation
-
Y. Gong, Y. Jia, T. K. Leung, A. Toshev, and S. Ioffe. Deep convolutional ranking for multilabel image annotation. In Proc. ICLR, 2014.
-
(2014)
Proc. ICLR
-
-
Gong, Y.1
Jia, Y.2
Leung, T.K.3
Toshev, A.4
Ioffe, S.5
-
7
-
-
84959243872
-
Improving image-sentence embeddings using large weakly annotated photo collections
-
Y. Gong, L. Wang, M. Hodosh, J. Hockenmaier, and S. Lazebnik. Improving image-sentence embeddings using large weakly annotated photo collections. In Proc. ECCV, 2014.
-
(2014)
Proc. ECCV
-
-
Gong, Y.1
Wang, L.2
Hodosh, M.3
Hockenmaier, J.4
Lazebnik, S.5
-
8
-
-
77953202699
-
Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation
-
M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. In Proc. ICCV, 2009.
-
(2009)
Proc. ICCV
-
-
Guillaumin, M.1
Mensink, T.2
Verbeek, J.3
Schmid, C.4
-
9
-
-
85083950659
-
Efficient learning of domain-invariant image representations
-
J. Hoffman, E. Rodner, J. Donahue, K. Saenko, and T. Darrell. Efficient learning of domain-invariant image representations. In Proc. ICLR, 2013.
-
(2013)
Proc. ICLR
-
-
Hoffman, J.1
Rodner, E.2
Donahue, J.3
Saenko, K.4
Darrell, T.5
-
10
-
-
84913555165
-
-
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding, 2014. http://arxiv.org/abs/1408.5093.
-
(2014)
Caffe: Convolutional Architecture for Fast Feature Embedding
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.6
Guadarrama, S.7
Darrell, T.8
-
11
-
-
84919772013
-
Recognizing image style
-
S. Karayev, M. Trentacoste, H. Han, A. Agarwala, T. Darrell, A. Hertzmann, and H. Winnemoeller. Recognizing image style. In Proc. BMVC, 2014.
-
(2014)
Proc. BMVC
-
-
Karayev, S.1
Trentacoste, M.2
Han, H.3
Agarwala, A.4
Darrell, T.5
Hertzmann, A.6
Winnemoeller, H.7
-
12
-
-
84876231242
-
ImageNet classification with deep convolutional neural networks
-
A. Krizhevsky, I. Sutskever, and G. E. Hinton. ImageNet Classification with Deep Convolutional Neural Networks. In NIPS, 2012.
-
(2012)
NIPS
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
13
-
-
85083602472
-
Classifying tag relevance with relevant positive and negative examples
-
X. Li and C. G. M. Snoek. Classifying tag relevance with relevant positive and negative examples. In Proc. MM, 2013.
-
(2013)
Proc. MM
-
-
Li, X.1
Snoek, C.G.M.2
-
14
-
-
84975263305
-
-
X. Li, T. Uricchio, L. Ballan, M. Bertini, C. G. M. Snoek, and A. del Bimbo. Socializing the semantic gap: A comparative study on image tag assignment, refinement and retreival, 2015. http://arxiv.org/abs/1503.08248.
-
(2015)
Socializing the Semantic Gap: A Comparative Study on Image Tag Assignment Refinement and Retreival
-
-
Li, X.1
Uricchio, T.2
Ballan, L.3
Bertini, M.4
Snoek, C.G.M.5
Del Bimbo, A.6
-
16
-
-
84976702763
-
A lexical database for english
-
ACM
-
G. A. Miller. Wordnet: A lexical database for english. Commun. ACM, 38(11), 1995.
-
(1995)
Commun
, vol.38
, pp. 11
-
-
Miller. Wordnet, G.A.1
-
17
-
-
85015456272
-
A sparse kernel relevance model for automatic image annotation
-
S. Moran and V. Lavrenko. A sparse kernel relevance model for automatic image annotation. Int J Multimed. Info Retr, 3(4), 2014.
-
(2014)
Int J Multimed. Info Retr
, vol.3
, pp. 4
-
-
Moran, S.1
Lavrenko, V.2
-
20
-
-
67649275535
-
What drives content tagging: The case of photos on flickr
-
O. Nov, M. Naaman, and C. Ye. What drives content tagging: The case of photos on flickr. In Proc. CHI, 2008.
-
(2008)
Proc. CHI
-
-
Nov, O.1
Naaman, M.2
Ye, C.3
-
21
-
-
84898828265
-
From large scale image categorization to entry-level categories
-
V. Ordonez, J. Deng, Y. Choi, A. C. Berg, and T. L. Berg. From large scale image categorization to entry-level categories. In Proc. ICCV, 2013.
-
(2013)
Proc. ICCV
-
-
Ordonez, V.1
Deng, J.2
Choi, Y.3
Berg, A.C.4
Berg, T.L.5
-
22
-
-
84900870389
-
The sun attribute database: Beyond categories for deeper scene understanding
-
G. Patterson, C. Xu, H. Su, and J. Hays. The sun attribute database: Beyond categories for deeper scene understanding. IJCV, 108:59-81, 2014.
-
(2014)
IJCV
, vol.108
, pp. 59-81
-
-
Patterson, G.1
Xu, C.2
Su, H.3
Hays, J.4
-
23
-
-
77951954464
-
Learning from crowds
-
V. C. Raykar, S. Y, L. H. Zhao, G. H. Valadez, C. Florin, L. Bogoni, and L. Moy. Learning from crowds. JMLR, 11:1297-1322, 2010.
-
(2011)
JMLR
, Issue.11
, pp. 1297-1322
-
-
Raykar, S.Y.V.C.1
Zhao, L.H.2
Valadez, G.H.3
Florin, C.4
Bogoni, L.5
Moy, L.6
-
24
-
-
85083952566
-
Training deep neural networks on noisy labels with bootstrapping
-
S. E. Reed, H. Lee, D. Anguelov, C. Szegedy, D. Erhan, and A. Rabinovich. Training deep neural networks on noisy labels with bootstrapping. In Proc. ICLR, 2015.
-
(2015)
Proc. ICLR
-
-
Reed, S.E.1
Lee, H.2
Anguelov, D.3
Szegedy, C.4
Erhan, D.5
Rabinovich, A.6
-
25
-
-
84909978410
-
-
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei. Imagenet large scale visual recognition challenge, 2014. http://arxiv.org/abs/1409.0575.
-
(2014)
Imagenet Large Scale Visual Recognition Challenge
-
-
Russakovsky, O.1
Deng, J.2
Su, H.3
Krause, J.4
Satheesh, S.5
Ma, S.6
Huang, Z.7
Karpathy, A.8
Khosla, A.9
Bernstein, M.10
Berg, A.C.11
Fei-Fei, L.12
-
26
-
-
85083605123
-
Unsupervised learning of visual sense models for polysemous words
-
K. Saenko and T. Darrell. Unsupervised learning of visual sense models for polysemous words. In Proc. NIPS, 2008.
-
(2008)
Proc. NIPS
-
-
Saenko, K.1
Darrell, T.2
-
28
-
-
85083950731
-
Training convolution networks with noisy labels
-
S. Sukhbaatar, J. Bruna, M. Paluri, L. Bourdev, and R. Fergus. Training convolution networks with noisy labels. In Proc. ICLR, 2015.
-
(2015)
Proc. ICLR
-
-
Sukhbaatar, S.1
Bruna, J.2
Paluri, M.3
Bourdev, L.4
Fergus, R.5
-
29
-
-
10844249670
-
Labeling images with a computer game
-
L. von Ahn and L. Dabbish. Labeling images with a computer game. In Proc. CHI, 2004.
-
(2004)
Proc. CHI
-
-
Von Ahn, L.1
Dabbish, L.2
-
30
-
-
77955988947
-
Sun database: Large-scale scene recognition from abbey to zoo
-
J. Xiao, J. Hays, K. Ehinger, A. Oliva, and A. Torralba. Sun database: Large-scale scene recognition from abbey to zoo. In Proc. CVPR, 2010.
-
(2011)
Proc. CVPR
-
-
Xiao, J.1
Hays, J.2
Ehinger, K.3
Oliva, A.4
Torralba, A.5
-
31
-
-
84937964578
-
Learning Deep Features for Scene Recognition using Places Database
-
B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva. Learning Deep Features for Scene Recognition using Places Database. In Proc. NIPS, 2014.
-
(2014)
Proc. NIPS
-
-
Zhou, B.1
Lapedriza, A.2
Xiao, J.3
Torralba, A.4
Oliva, A.5
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