-
2
-
-
84973882857
-
Predicting deep zero-shot convolutional neural networks using textual descriptions
-
J. L. Ba, K. Swersky, S. Fidler, and R. Salakhutdinov. Predicting Deep Zero-Shot Convolutional Neural Networks using Textual Descriptions. In ICCV, 2015.
-
(2015)
ICCV
-
-
Ba, J.L.1
Swersky, K.2
Fidler, S.3
Salakhutdinov, R.4
-
3
-
-
85021776053
-
Toward an architecture for never-ending language learning
-
A. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. H. Jr., and T. M. Mitchell. Toward an architecture for never-ending language learning. In AAAI, 2010.
-
(2010)
AAAI
-
-
Carlson, A.1
Betteridge, J.2
Kisiel, B.3
Settles, B.4
Mitchell, T.M.5
-
5
-
-
85041928731
-
Predicting visual exemplars of unseen classes for zero-shot learning
-
S. Changpinyo, W.-L. Chao, and F. Sha. Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning. In ICCV, 2017.
-
(2017)
ICCV
-
-
Changpinyo, S.1
Chao, W.-L.2
Sha, F.3
-
6
-
-
85041895800
-
An empirical study and analysis of generalized zero-shot learning for object recognition in the wild
-
W.-L. Chao, S. Changpinyo, B. Gong, and F. Sha. An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild. In ECCV, 2016.
-
(2016)
ECCV
-
-
Chao, W.-L.1
Changpinyo, S.2
Gong, B.3
Sha, F.4
-
7
-
-
85072028231
-
Return of the devil in the details: Delving deep into convolutional nets
-
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman. Return of the devil in the details: Delving deep into convolutional nets. In BMVC, 2014.
-
(2014)
BMVC
-
-
Chatfield, K.1
Simonyan, K.2
Vedaldi, A.3
Zisserman, A.4
-
8
-
-
84898803720
-
Neil: Extracting visual knowledge from web data
-
X. Chen, A. Shrivastava, and A. Gupta. Neil: Extracting visual knowledge from web data. ICCV, 2013.
-
(2013)
ICCV
-
-
Chen, X.1
Shrivastava, A.2
Gupta, A.3
-
9
-
-
84925408575
-
Large-scale object classification using label relation graphs
-
J. Deng, N. Ding, Y. Jia, A. Frome, K. Murphy, S. Bengio, Y. Li, H. Neven, and H. Adam. Large-Scale Object Classification Using Label Relation Graphs. In ECCV, 2014.
-
(2014)
ECCV
-
-
Deng, J.1
Ding, N.2
Jia, Y.3
Frome, A.4
Murphy, K.5
Bengio, S.6
Li, Y.7
Neven, H.8
Adam, H.9
-
10
-
-
84898803425
-
Write a classifier: Zero-shot learning using purely textual descriptions
-
M. Elhoseiny, B. Saleh, and A. Elgammal. Write a Classifier: Zero-Shot Learning Using Purely Textual Descriptions. In ICCV, 2013.
-
(2013)
ICCV
-
-
Elhoseiny, M.1
Saleh, B.2
Elgammal, A.3
-
12
-
-
80052894360
-
Semantic label sharing for learning with many categories
-
R. Fergus, H. Bernal, Y. Weiss, and A. Torralba. Semantic Label Sharing for Learning with Many Categories. In ECCV, 2010.
-
(2010)
ECCV
-
-
Fergus, R.1
Bernal, H.2
Weiss, Y.3
Torralba, A.4
-
13
-
-
84898958665
-
Devise: A deep visual-semantic embedding model
-
A. Frome, G. Corrado, J. Shlens, S. Bengio, J. Dean, and T. Mikolov. Devise: A deep visual-semantic embedding model. In NIPS, 2013.
-
(2013)
NIPS
-
-
Frome, A.1
Corrado, G.2
Shlens, J.3
Bengio, S.4
Dean, J.5
Mikolov, T.6
-
14
-
-
84986246085
-
Semi-supervised vocabulary-informed learning
-
Y. Fu and L. Sigal. Semi-supervised Vocabulary-informed Learning. In CVPR, 2016.
-
(2016)
CVPR
-
-
Fu, Y.1
Sigal, L.2
-
15
-
-
84940993365
-
Zero-shot object recognition by semantic manifold distance
-
Z. Fu, T. Xiang, E. Kodirov, and S. Gong. Zero-Shot Object Recognition by Semantic Manifold Distance. In CVPR, 2015.
-
(2015)
CVPR
-
-
Fu, Z.1
Xiang, T.2
Kodirov, E.3
Gong, S.4
-
16
-
-
85078801584
-
Low-shot visual recognition by shrinking and hallucinating features
-
B. Hariharan and R. Girshick. Low-shot Visual Recognition by Shrinking and Hallucinating Features. In CoRR, 2017.
-
(2017)
CoRR
-
-
Hariharan, B.1
Girshick, R.2
-
17
-
-
84986274465
-
Deep residual learning for image recognition
-
K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. In CVPR, 2016.
-
(2016)
CVPR
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
18
-
-
85019222252
-
Local similarity-aware deep feature embedding
-
C. Huang, C. C. Loy, and X. Tang. Local similarity-aware deep feature embedding. In NIPS, 2016.
-
(2016)
NIPS
-
-
Huang, C.1
Loy, C.C.2
Tang, X.3
-
19
-
-
84937954530
-
Zero-shot recognition with unreliable attributes
-
D. Jayaraman and K. Grauman. Zero-shot recognition with unreliable attributes. In NIPS, pages 3464-3472, 2014.
-
(2014)
NIPS
, pp. 3464-3472
-
-
Jayaraman, D.1
Grauman, K.2
-
20
-
-
85047021378
-
-
A. Joulin, E. Grave, P. Bojanowski, M. Douze, H. Jégou, and T. Mikolov. Fasttext.zip: Compressing text classification models. arXiv preprint arXiv:1612.03651, 2016.
-
(2016)
Fasttext.zip: Compressing Text Classification Models
-
-
Joulin, A.1
Grave, E.2
Bojanowski, P.3
Douze, M.4
Jégou, H.5
Mikolov, T.6
-
21
-
-
85083951076
-
Adam: A method for stochastic optimization
-
D. Kingma and J. Ba. Adam: A method for stochastic optimization. CoRR, abs/1412.6980, 2014.
-
(2014)
CoRR, abs/1412.6980
-
-
Kingma, D.1
Ba, J.2
-
22
-
-
85086180249
-
Semi-supervised classification with graph convolutional networks
-
T. N. Kipf and M. Welling. Semi-supervised classification with graph convolutional networks. ICLR, 2017.
-
(2017)
ICLR
-
-
Kipf, T.N.1
Welling, M.2
-
23
-
-
85044294853
-
Semantic autoencoder for zero-shot learning
-
E. Kodirov, T. Xiang, and S. Gong. Semantic Autoencoder for Zero-Shot Learning. In CVPR, 2017.
-
(2017)
CVPR
-
-
Kodirov, E.1
Xiang, T.2
Gong, S.3
-
24
-
-
70450172710
-
Learning to detect unseen object classes by between-class attribute transfer
-
C. H. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
-
(2009)
CVPR
-
-
Lampert, C.H.1
Nickisch, H.2
Harmeling, S.3
-
25
-
-
84894522762
-
Attribute-based classification for zero-shot visual object categorization
-
C. H. Lampert, H. Nickisch, and S. Harmeling. Attribute-Based Classification for Zero-Shot Visual Object Categorization. In TPAMI, 2014.
-
(2014)
TPAMI
-
-
Lampert, C.H.1
Nickisch, H.2
Harmeling, S.3
-
26
-
-
85006110312
-
Unsupervised learning on neural network outputs: With application in zero-shot learning
-
Y. Lu. Unsupervised learning on neural network outputs: With application in zero-shot learning. In IJCAI, 2016.
-
(2016)
IJCAI
-
-
Lu, Y.1
-
27
-
-
84893676344
-
Rectifier nonlinearities improve neural network acoustic models
-
A. L. Maas, A. Y. Hannun, and A. Y. Ng. Rectifier nonlinearities improve neural network acoustic models. In ICML, 2013.
-
(2013)
ICML
-
-
Maas, A.L.1
Hannun, A.Y.2
Ng, A.Y.3
-
29
-
-
85041905615
-
The more you know: Using knowledge graphs for image classification
-
K. Marino, R. Salakhutdinov, and A. Gupta. The More You Know: Using Knowledge Graphs for Image Classification. In CVPR, 2017.
-
(2017)
CVPR
-
-
Marino, K.1
Salakhutdinov, R.2
Gupta, A.3
-
30
-
-
84883488616
-
Metric learning for large scale image classification: Generalizing to new classes at near-zero cost
-
T. Mensink, J. Verbeek, F. Perronnin, and G. Csurka. Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost. In ECCV, 2012.
-
(2012)
ECCV
-
-
Mensink, T.1
Verbeek, J.2
Perronnin, F.3
Csurka, G.4
-
31
-
-
85083951332
-
Efficient estimation of word representations in vector space
-
T. Mikolov, K. Chen, G. Corrado, and J. Dean. Efficient estimation of word representations in vector space. ICLR, 2013.
-
(2013)
ICLR
-
-
Mikolov, T.1
Chen, K.2
Corrado, G.3
Dean, J.4
-
32
-
-
84976702763
-
Wordnet: A lexical database for english
-
G. A. Miller. Wordnet: A lexical database for english. Communications of the ACM, 38(11):39-41, 1995.
-
(1995)
Communications of the ACM
, vol.38
, Issue.11
, pp. 39-41
-
-
Miller, G.A.1
-
33
-
-
85044323744
-
From red wine to red tomato: Composition with context
-
I. Misra, A. Gupta, and M. Hebert. From Red Wine to Red Tomato: Composition with Context. In CVPR, 2017.
-
(2017)
CVPR
-
-
Misra, I.1
Gupta, A.2
Hebert, M.3
-
34
-
-
85083952206
-
Zero-shot learning by convex combination of semantic embeddings
-
M. Norouzi, T. Mikolov, S. Bengio, Y. Singer, J. Shlens, A. Frome, G. S. Corrado, and J. Dean. Zero-shot learning by convex combination of semantic embeddings. In ICLR, 2014.
-
(2014)
ICLR
-
-
Norouzi, M.1
Mikolov, T.2
Bengio, S.3
Singer, Y.4
Shlens, J.5
Frome, A.6
Corrado, G.S.7
Dean, J.8
-
36
-
-
84961289992
-
Glove: Global vectors for word representation
-
J. Pennington, R. Socher, and C. D. Manning. Glove: Global vectors for word representation. In EMNLP, pages 1532-1543, 2014.
-
(2014)
EMNLP
, pp. 1532-1543
-
-
Pennington, J.1
Socher, R.2
Manning, C.D.3
-
37
-
-
84986290328
-
Less is more: Zero-shot learning from online textual documents with noise suppression
-
R. Qiao, L. Liu, C. Shen, and A. van den Hengel. Less is more: Zero-shot learning from online textual documents with noise suppression. In CVPR, 2016.
-
(2016)
CVPR
-
-
Qiao, R.1
Liu, L.2
Shen, C.3
Vanden Hengel, A.4
-
38
-
-
84899001511
-
Transfer learning in a transductive setting
-
M. Rohrbach, S. Ebert, and B. Schiele. Transfer learning in a transductive setting. In NIPS, 2013.
-
(2013)
NIPS
-
-
Rohrbach, M.1
Ebert, S.2
Schiele, B.3
-
39
-
-
80052892795
-
Evaluating knowledge transfer and zero-shot learning in a large-scale setting
-
M. Rohrbach, M. Stark, and B. Schiele. Evaluating Knowledge Transfer and Zero-Shot Learning in a Large-Scale Setting. In CVPR, 2011.
-
(2011)
CVPR
-
-
Rohrbach, M.1
Stark, M.2
Schiele, B.3
-
40
-
-
77955989949
-
What helps where-And why? Semantic relatedness for knowledge transfer
-
M. Rohrbach, M. Stark, G. Szarvas, I. Gurevych, and B. Schiele. What helps where-and why? semantic relatedness for knowledge transfer. In CVPR, 2010.
-
(2010)
CVPR
-
-
Rohrbach, M.1
Stark, M.2
Szarvas, G.3
Gurevych, I.4
Schiele, B.5
-
41
-
-
84969931523
-
An embarrassingly simple approach to zero-shot learning
-
B. Romera-Paredes and P. H. S. Torr. An embarrassingly simple approach to zero-shot learning. In ICML, 2015.
-
(2015)
ICML
-
-
Romera-Paredes, B.1
Torr, P.H.S.2
-
42
-
-
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, et al. Imagenet large scale visual recognition challenge. IJCV, 115(3):211-252, 2015.
-
(2015)
IJCV
, vol.115
, Issue.3
, pp. 211-252
-
-
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
-
43
-
-
80052905403
-
Learning to share visual appearance for multiclass object detection
-
R. Salakhutdinov, A. Torralba, and J. Tenenbaum. Learning to Share Visual Appearance for Multiclass Object Detection. In CVPR, 2011.
-
(2011)
CVPR
-
-
Salakhutdinov, R.1
Torralba, A.2
Tenenbaum, J.3
-
45
-
-
85041923826
-
Revisiting unreasonable effectiveness of data in deep learning era
-
C. Sun, A. Shrivastava, S. Singh, and A. Gupta. Revisiting unreasonable effectiveness of data in deep learning era. In ICCV, 2017.
-
(2017)
ICCV
-
-
Sun, C.1
Shrivastava, A.2
Singh, S.3
Gupta, A.4
-
46
-
-
84937522268
-
Going deeper with convolutions
-
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. Going Deeper with Convolutions. In CVPR, 2015.
-
(2015)
CVPR
-
-
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
-
47
-
-
85053003919
-
FVQA: Fact-based visual question answering
-
P. Wang, Q. Wu, C. Shen, A. van den Hengel, and A. Dick. FVQA: Fact-based Visual Question Answering. In CoRR, 2016.
-
(2016)
CoRR
-
-
Wang, P.1
Wu, Q.2
Shen, C.3
Vanden Hengel, A.4
Dick, A.5
-
48
-
-
77955654853
-
Large scale image annotation: Learning to rank with joint word-image embeddings
-
J. Weston, S. Bengio, and N. Usunier. Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings. In ECML, 2010.
-
(2010)
ECML
-
-
Weston, J.1
Bengio, S.2
Usunier, N.3
-
49
-
-
84986320870
-
Ask me anything: Free-form visual question answering based on knowledge from external sources
-
Q. Wu, P. Wang, C. Shen, A. Dick, and A. van den Hengel. Ask me anything: Free-form visual question answering based on knowledge from external sources. In CVPR, 2016.
-
(2016)
CVPR
-
-
Wu, Q.1
Wang, P.2
Shen, C.3
Dick, A.4
Van Den Hengel, A.5
-
50
-
-
85041909958
-
Zero-shot learning-The good, the bad and the ugly
-
Y. Xian, B. Schiele, and Z. Akata. Zero-Shot Learning-The Good, the Bad and the Ugly. In CVPR, 2017.
-
(2017)
CVPR
-
-
Xian, Y.1
Schiele, B.2
Akata, Z.3
-
51
-
-
85013858782
-
Empirical evaluation of rectified activations in convolutional network
-
B. Xu, N. Wang, T. Chen, and M. Li. Empirical evaluation of rectified activations in convolutional network. CoRR, abs/1505.00853, 2015.
-
(2015)
CoRR, abs/1505.00853
-
-
Xu, B.1
Wang, N.2
Chen, T.3
Li, M.4
-
52
-
-
84997706245
-
Revisiting semisupervised learning with graph embeddings
-
Z. Yang, W. Cohen, and R. Salakhutdinov. Revisiting semisupervised learning with graph embeddings. In ICML, 2016.
-
(2016)
ICML
-
-
Yang, Z.1
Cohen, W.2
Salakhutdinov, R.3
-
53
-
-
85041928291
-
Learning a deep embedding model for zero-shot learning
-
L. Zhang, T. Xiang, and S. Gong. Learning a deep embedding model for zero-shot learning. In CVPR, 2017.
-
(2017)
CVPR
-
-
Zhang, L.1
Xiang, T.2
Gong, S.3
-
54
-
-
84973910934
-
Zero-shot learning via semantic similarity embedding
-
Z. Zhang and V. Saligrama. Zero-shot learning via semantic similarity embedding. In ICCV, 2015.
-
(2015)
ICCV
-
-
Zhang, Z.1
Saligrama, V.2
-
55
-
-
84986292720
-
Zero-shot learning via joint latent similarity embedding
-
Z. Zhang and V. Saligrama. Zero-shot learning via joint latent similarity embedding. In CVPR, 2016.
-
(2016)
CVPR
-
-
Zhang, Z.1
Saligrama, V.2
|