-
1
-
-
84973913759
-
-
YFCC dataset
-
YFCC dataset. labs. yahoo. com/news/yfcc100m/.
-
-
-
-
2
-
-
84973389608
-
Analyzing the performance of multilayer neural networks for object recognition
-
P. Agrawal, R. Girshick, and J. Malik. Analyzing the performance of multilayer neural networks for object recognition. In ECCV. 2014.
-
(2014)
ECCV
-
-
Agrawal, P.1
Girshick, R.2
Malik, J.3
-
4
-
-
70449602122
-
Finding iconic images
-
T. L. Berg and A. C. Berg. Finding iconic images. In CVPRW, 2009.
-
(2009)
CVPRW
-
-
Berg, T.L.1
Berg, A.C.2
-
7
-
-
85161970767
-
Exploiting weakly-labeled web images to improve object classification: A domain adaptation approach
-
A. Bergamo and L. Torresani. Exploiting weakly-labeled web images to improve object classification: A domain adaptation approach. In NIPS, 2010.
-
(2010)
NIPS
-
-
Bergamo, A.1
Torresani, L.2
-
9
-
-
84898803720
-
NEIL: Extracting visual knowledge from web data
-
X. Chen, A. Shrivastava, and A. Gupta. NEIL: Extracting visual knowledge from web data. In ICCV, 2013.
-
(2013)
ICCV
-
-
Chen, X.1
Shrivastava, A.2
Gupta, A.3
-
10
-
-
84911458493
-
Enriching visual knowledge bases via object discovery and segmentation
-
X. Chen, A. Shrivastava, and A. Gupta. Enriching visual knowledge bases via object discovery and segmentation. In CVPR, 2014.
-
(2014)
CVPR
-
-
Chen, X.1
Shrivastava, A.2
Gupta, A.3
-
11
-
-
34948861144
-
Weakly supervised learning of part-based spatial models for visual object recognition
-
D. J. Crandall and D. P. Huttenlocher. Weakly supervised learning of part-based spatial models for visual object recognition. In ECCV. 2006.
-
(2006)
ECCV
-
-
Crandall, D.J.1
Huttenlocher, D.P.2
-
12
-
-
84867062047
-
Weakly supervised localization and learning with generic knowledge
-
T. Deselaers, B. Alexe, and V. Ferrari. Weakly supervised localization and learning with generic knowledge. IJCV, 2012.
-
(2012)
IJCV
-
-
Deselaers, T.1
Alexe, B.2
Ferrari, V.3
-
13
-
-
84911368326
-
Learning everything about anything: Webly-supervised visual concept learning
-
S. K. Divvala, A. Farhadi, and C. Guestrin. Learning everything about anything: Webly-supervised visual concept learning. In CVPR, 2014.
-
(2014)
CVPR
-
-
Divvala, S.K.1
Farhadi, A.2
Guestrin, C.3
-
14
-
-
84911409936
-
The pascal visual object classes (voc) challenge
-
M. Everingham, L. VanGool, C. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. IJCV 10.
-
IJCV
, vol.10
-
-
Everingham, M.1
VanGool, L.2
Williams, C.3
Winn, J.4
Zisserman, A.5
-
15
-
-
77956002586
-
Harvesting large-scale weaklytagged image databases from the web
-
J. Fan, Y. Shen, N. Zhou, and Y. Gao. Harvesting large-scale weaklytagged image databases from the web. In CVPR, 2010.
-
(2010)
CVPR
-
-
Fan, J.1
Shen, Y.2
Zhou, N.3
Gao, Y.4
-
18
-
-
24644456520
-
A visual category filter for google images
-
R. Fergus, P. Perona, and A. Zisserman. A visual category filter for google images. In ECCV. 2004.
-
(2004)
ECCV
-
-
Fergus, R.1
Perona, P.2
Zisserman, A.3
-
19
-
-
84911400494
-
Rich feature hierarchies for accurate object detection and semantic segmentation
-
R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014.
-
(2014)
CVPR
-
-
Girshick, R.1
Donahue, J.2
Darrell, T.3
Malik, J.4
-
20
-
-
84951930934
-
Conceptmap: Mining noisy web data for concept learning
-
E. Golge and P. Duygulu. Conceptmap: Mining noisy web data for concept learning. In ECCV. 2014.
-
(2014)
ECCV
-
-
Golge, E.1
Duygulu, P.2
-
22
-
-
84887395819
-
Discriminative decorrelation for clustering and classification
-
B. Hariharan, J. Malik, and D. Ramanan. Discriminative decorrelation for clustering and classification. In ECCV.
-
ECCV
-
-
Hariharan, B.1
Malik, J.2
Ramanan, D.3
-
23
-
-
85009867858
-
Caffe: Convolutional architecture for fast feature embedding
-
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding. In ACM MM, 2014.
-
(2014)
ACM MM
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.6
Guadarrama, S.7
Darrell, T.8
-
24
-
-
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
-
25
-
-
85161967298
-
Self-paced learning for latent variable models
-
M. P. Kumar, B. Packer, and D. Koller. Self-paced learning for latent variable models. In NIPS, 2010.
-
(2010)
NIPS
-
-
Kumar, M.P.1
Packer, B.2
Koller, D.3
-
26
-
-
80052880043
-
Learning the easy things first: Self-paced visual category discovery
-
Y. J. Lee and K. Grauman. Learning the easy things first: Self-paced visual category discovery. In CVPR, 2011.
-
(2011)
CVPR
-
-
Lee, Y.J.1
Grauman, K.2
-
27
-
-
77951297833
-
OPTIMOL: Automatic online picture collection via incremental model learning
-
L.-J. Li and L. Fei-Fei. OPTIMOL: Automatic online picture collection via incremental model learning. IJCV, 2010.
-
(2010)
IJCV
-
-
Li, L.-J.1
Fei-Fei, L.2
-
28
-
-
84887327253
-
Harvesting mid-level visual concepts from large-scale internet images
-
Q. Li, J. Wu, and Z. Tu. Harvesting mid-level visual concepts from large-scale internet images. In CVPR, 2013.
-
(2013)
CVPR
-
-
Li, Q.1
Wu, J.2
Tu, Z.3
-
29
-
-
84937834115
-
Microsoft coco: Common objects in context
-
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick. Microsoft coco: Common objects in context. In ECCV. 2014.
-
(2014)
ECCV
-
-
Lin, T.-Y.1
Maire, M.2
Belongie, S.3
Hays, J.4
Perona, P.5
Ramanan, D.6
Dollár, P.7
Zitnick, C.L.8
-
30
-
-
84877751270
-
Learning about canonical views from internet image collections
-
E. Mezuman and Y. Weiss. Learning about canonical views from internet image collections. In NIPS, 2012.
-
(2012)
NIPS
-
-
Mezuman, E.1
Weiss, Y.2
-
32
-
-
84919730581
-
Weakly supervised object recognition with convolutional neural networks
-
M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Weakly supervised object recognition with convolutional neural networks. Technical report, 2014.
-
(2014)
Technical Report
-
-
Oquab, M.1
Bottou, L.2
Laptev, I.3
Sivic, J.4
-
33
-
-
85162522202
-
Im2text: Describing images using 1 million captioned photographs
-
V. Ordonez, G. Kulkarni, and T. L. Berg. Im2text: Describing images using 1 million captioned photographs. In NIPS, 2011.
-
(2011)
NIPS
-
-
Ordonez, V.1
Kulkarni, G.2
Berg, T.L.3
-
34
-
-
84856650974
-
Scene recognition and weakly supervised object localization with deformable part-based models
-
M. Pandey and S. Lazebnik. Scene recognition and weakly supervised object localization with deformable part-based models. In ICCV, 2011.
-
(2011)
ICCV
-
-
Pandey, M.1
Lazebnik, S.2
-
38
-
-
51849144124
-
Computing iconic summaries of general visual concepts
-
R. Raguram and S. Lazebnik. Computing iconic summaries of general visual concepts. In CVPRW, 2008.
-
(2008)
CVPRW
-
-
Raguram, R.1
Lazebnik, S.2
-
40
-
-
84973287072
-
-
arXiv:1412. 6596
-
S. Reed, H. Lee, D. Anguelov, C. Szegedy, D. Erhan, and A. Rabinovich. Training deep neural networks on noisy labels with bootstrapping. ArXiv:1412. 6596, 2014.
-
(2014)
Training Deep Neural Networks on Noisy Labels with Bootstrapping
-
-
Reed, S.1
Lee, H.2
Anguelov, D.3
Szegedy, C.4
Erhan, D.5
Rabinovich, A.6
-
41
-
-
84909978410
-
-
arXiv:1409. 0575
-
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al. Imagenet large scale visual recognition challenge. ArXiv:1409. 0575, 2014.
-
(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
-
42
-
-
77955111164
-
Unsupervised learning of visual sense models for polysemous words
-
K. Saenko and T. Darrell. Unsupervised learning of visual sense models for polysemous words. In NIPS, 2009.
-
(2009)
NIPS
-
-
Saenko, K.1
Darrell, T.2
-
46
-
-
0345414182
-
Video google: A text retrieval approach to object matching in videos
-
J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In ICCV, 2003.
-
(2003)
ICCV
-
-
Sivic, J.1
Zisserman, A.2
-
47
-
-
0034498523
-
Content-based image retrieval at the end of the early years
-
A. W. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-based image retrieval at the end of the early years. TPAMI, 2000.
-
(2000)
TPAMI
-
-
Smeulders, A.W.1
Worring, M.2
Santini, S.3
Gupta, A.4
Jain, R.5
-
48
-
-
84919792468
-
On learning to localize objects with minimal supervision
-
H. O. Song, R. Girshick, S. Jegelka, J. Mairal, Z. Harchaoui, and T. Darrell. On learning to localize objects with minimal supervision. In ICML.
-
ICML
-
-
Song, H.O.1
Girshick, R.2
Jegelka, S.3
Mairal, J.4
Harchaoui, Z.5
Darrell, T.6
-
50
-
-
84964983441
-
-
arXiv:1409. 4842
-
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. Going deeper with convolutions. ArXiv:1409. 4842, 2014.
-
(2014)
Going Deeper with Convolutions
-
-
Szegedy, C.1
Liu, W.2
Jia, Y.3
Sermanet, P.4
Reed, S.5
Anguelov, D.6
Erhan, D.7
Vanhoucke, V.8
Rabinovich, A.9
-
51
-
-
84911198048
-
Deepface: Closing the gap to human-level performance in face verification
-
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf. Deepface: Closing the gap to human-level performance in face verification. In CVPR, 2014.
-
(2014)
CVPR
-
-
Taigman, Y.1
Yang, M.2
Ranzato, M.3
Wolf, L.4
-
52
-
-
80052908300
-
Unbiased look at dataset bias
-
A. Torralba and A. A. Efros. Unbiased look at dataset bias. In CVPR, 2011.
-
(2011)
CVPR
-
-
Torralba, A.1
Efros, A.A.2
-
53
-
-
80052896768
-
Efficient object category recognition using classemes
-
L. Torresani, M. Szummer, and A. Fitzgibbon. Efficient object category recognition using classemes. In ECCV. 2010.
-
(2010)
ECCV
-
-
Torresani, L.1
Szummer, M.2
Fitzgibbon, A.3
-
54
-
-
51949096901
-
Keywords to visual categories: Multiple-instance learning forweakly supervised object categorization
-
S. Vijayanarasimhan and K. Grauman. Keywords to visual categories: Multiple-instance learning forweakly supervised object categorization. In CVPR, 2008.
-
(2008)
CVPR
-
-
Vijayanarasimhan, S.1
Grauman, K.2
-
55
-
-
84956604127
-
Weakly supervised object localization with latent category learning
-
C. Wang, W. Ren, K. Huang, and T. Tan. Weakly supervised object localization with latent category learning. In ECCV. 2014.
-
(2014)
ECCV
-
-
Wang, C.1
Ren, W.2
Huang, K.3
Tan, T.4
-
56
-
-
54849395400
-
Annotating images by mining image search results
-
X.-J. Wang, L. Zhang, X. Li, and W.-Y. Ma. Annotating images by mining image search results. TPAMI, 2008.
-
(2008)
TPAMI
-
-
Wang, X.-J.1
Zhang, L.2
Li, X.3
Ma, W.-Y.4
-
57
-
-
84951972106
-
Well begun is half done: Generating high-quality seeds for automatic image dataset construction from web
-
Y. Xia, X. Cao, F. Wen, and J. Sun. Well begun is half done: Generating high-quality seeds for automatic image dataset construction from web. In ECCV. 2014.
-
(2014)
ECCV
-
-
Xia, Y.1
Cao, X.2
Wen, F.3
Sun, J.4
-
58
-
-
77955988947
-
Sun database: Large-scale scene recognition from abbey to zoo
-
J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba. Sun database: Large-scale scene recognition from abbey to zoo. In CVPR, 2010.
-
(2010)
CVPR
-
-
Xiao, J.1
Hays, J.2
Ehinger, K.A.3
Oliva, A.4
Torralba, A.5
-
59
-
-
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 NIPS, 2014.
-
(2014)
NIPS
-
-
Zhou, B.1
Lapedriza, A.2
Xiao, J.3
Torralba, A.4
Oliva, A.5
-
60
-
-
84952018709
-
Edge boxes: Locating object proposals from edges
-
C. L. Zitnick and P. Dollár. Edge boxes: Locating object proposals from edges. In ECCV. 2014.
-
(2014)
ECCV
-
-
Zitnick, C.L.1
Dollár, P.2
|