-
3
-
-
84919881041
-
Decaf: A deep convolutional activation feature for generic visual recognition
-
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell. Decaf: A deep convolutional activation feature for generic visual recognition. International Conference on Machine Learning, 2014.
-
(2014)
International Conference on Machine Learning
-
-
Donahue, J.1
Jia, Y.2
Vinyals, O.3
Hoffman, J.4
Zhang, N.5
Tzeng, E.6
Darrell, T.7
-
5
-
-
50949133669
-
Liblinear: A library for large linear classification
-
R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. Liblinear: A library for large linear classification. The Journal of Machine Learning Research, 2008.
-
(2008)
The Journal of Machine Learning Research
-
-
Fan, R.-E.1
Chang, K.-W.2
Hsieh, C.-J.3
Wang, X.-R.4
Lin, C.-J.5
-
6
-
-
34047174674
-
Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
-
L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories. Computer Vision and Image Understanding, 2007.
-
(2007)
Computer Vision and Image Understanding
-
-
Fei-Fei, L.1
Fergus, R.2
Perona, P.3
-
7
-
-
85099639125
-
Local alignments for fine-grained categorization
-
E. Gavves, B. Fernando, C. G. Snoek, A. W. Smeulders, and T. Tuytelaars. Local alignments for fine-grained categorization. Int'l Journal of Computer Vision, 2014.
-
(2014)
Int'l Journal of Computer Vision
-
-
Gavves, E.1
Fernando, B.2
Snoek, C.G.3
Smeulders, A.W.4
Tuytelaars, T.5
-
8
-
-
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. Proc. CVPR, 2014.
-
(2014)
Proc. CVPR
-
-
Girshick, R.1
Donahue, J.2
Darrell, T.3
Malik, J.4
-
11
-
-
33845572523
-
Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
-
S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. Proc. CVPR, 2006.
-
(2006)
Proc. CVPR
-
-
Lazebnik, S.1
Schmid, C.2
Ponce, J.3
-
12
-
-
50649103674
-
What, where and who? Classifying events by scene and object recognition
-
L.-J. Li and L. Fei-Fei. What, where and who? classifying events by scene and object recognition. Proc. ICCV, 2007.
-
(2007)
Proc. ICCV
-
-
Li, L.-J.1
Fei-Fei, L.2
-
14
-
-
84959213675
-
Understanding deep image representations by inverting them
-
A. Mahendran and A. Vedaldi. Understanding deep image representations by inverting them. Proc. CVPR, 2015.
-
(2015)
Proc. CVPR
-
-
Mahendran, A.1
Vedaldi, A.2
-
15
-
-
84911449395
-
Learning and transferring mid-level image representations using convolutional neural networks
-
M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Learning and transferring mid-level image representations using convolutional neural networks. Proc. CVPR, 2014.
-
(2014)
Proc. CVPR
-
-
Oquab, M.1
Bottou, L.2
Laptev, I.3
Sivic, J.4
-
16
-
-
84953933150
-
Is object localization for free? Weakly-supervised learning with convolutional neural networks
-
M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Is object localization for free? weakly-supervised learning with convolutional neural networks. Proc. CVPR, 2015.
-
(2015)
Proc. CVPR
-
-
Oquab, M.1
Bottou, L.2
Laptev, I.3
Sivic, J.4
-
17
-
-
84866637964
-
Sun attribute database: Discovering, annotating, and recognizing scene attributes
-
G. Patterson and J. Hays. Sun attribute database: Discovering, annotating, and recognizing scene attributes. Proc. CVPR, 2012.
-
(2012)
Proc. CVPR
-
-
Patterson, G.1
Hays, J.2
-
21
-
-
84947041871
-
Imagenet large scale visual recognition challenge
-
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. In Int'l Journal of Computer Vision, 2015.
-
(2015)
Int'l Journal of Computer Vision
-
-
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
-
22
-
-
84906347546
-
-
arXiv preprint arXiv:1312.6229
-
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. arXiv preprint arXiv:1312.6229, 2013.
-
(2013)
Overfeat: Integrated Recognition, Localization and Detection Using Convolutional Networks
-
-
Sermanet, P.1
Eigen, D.2
Zhang, X.3
Mathieu, M.4
Fergus, R.5
LeCun, Y.6
-
25
-
-
85009879494
-
-
arXiv preprint 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 preprint 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
-
27
-
-
80052891795
-
Caltech-ucsd birds 200
-
California Institute of Technology
-
P. Welinder, S. Branson, T. Mita, C. Wah, F. Schroff, S. Belongie, and P. Perona. Caltech-UCSD Birds 200. Technical report, California Institute of Technology, 2010.
-
(2010)
Technical Report
-
-
Welinder, P.1
Branson, S.2
Mita, T.3
Wah, C.4
Schroff, F.5
Belongie, S.6
Perona, P.7
-
28
-
-
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. Proc. CVPR, 2010.
-
(2010)
Proc. CVPR
-
-
Xiao, J.1
Hays, J.2
Ehinger, K.A.3
Oliva, A.4
Torralba, A.5
-
29
-
-
84856672971
-
Human action recognition by learning bases of action attributes and parts
-
B. Yao, X. Jiang, A. Khosla, A. L. Lin, L. Guibas, and L. Fei-Fei. Human action recognition by learning bases of action attributes and parts. Proc. ICCV, 2011.
-
(2011)
Proc. ICCV
-
-
Yao, B.1
Jiang, X.2
Khosla, A.3
Lin, A.L.4
Guibas, L.5
Fei-Fei, L.6
-
30
-
-
84921476116
-
Visualizing and understanding convolutional networks
-
M. D. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. Proc. ECCV, 2014.
-
(2014)
Proc. ECCV
-
-
Zeiler, M.D.1
Fergus, R.2
-
32
-
-
84898819241
-
Deformable part descriptors for fine-grained recognition and attribute prediction
-
N. Zhang, R. Farrell, F. Iandola, and T. Darrell. Deformable part descriptors for fine-grained recognition and attribute prediction. Proc. ICCV, 2013.
-
(2013)
Proc. ICCV
-
-
Zhang, N.1
Farrell, R.2
Iandola, F.3
Darrell, T.4
-
33
-
-
84959187860
-
Conceptlearner: Discovering visual concepts from weakly labeled image collections
-
B. Zhou, V. Jagadeesh, and R. Piramuthu. Conceptlearner: Discovering visual concepts from weakly labeled image collections. Proc. CVPR, 2015.
-
(2015)
Proc. CVPR
-
-
Zhou, B.1
Jagadeesh, V.2
Piramuthu, R.3
-
34
-
-
85083952996
-
Object detectors emerge in deep scene cnns
-
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba. Object detectors emerge in deep scene cnns. International Conference on Learning Representations, 2015.
-
(2015)
International Conference on Learning Representations
-
-
Zhou, B.1
Khosla, A.2
Lapedriza, A.3
Oliva, A.4
Torralba, A.5
-
35
-
-
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 Advances in Neural Information Processing Systems, 2014.
-
(2014)
Advances in Neural Information Processing Systems
-
-
Zhou, B.1
Lapedriza, A.2
Xiao, J.3
Torralba, A.4
Oliva, A.5
-
36
-
-
84986301525
-
-
arXiv preprint arXiv:1512.02167
-
B. Zhou, Y. Tian, S. Sukhbaatar, A. Szlam, and R. Fergus. Simple baseline for visual question answering. arXiv preprint arXiv:1512.02167, 2015.
-
(2015)
Simple Baseline for Visual Question Answering
-
-
Zhou, B.1
Tian, Y.2
Sukhbaatar, S.3
Szlam, A.4
Fergus, R.5
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