-
1
-
-
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
-
2
-
-
84911409986
-
Seeing 3D chairs: Exemplar part-based 2D-3D alignment using a large dataset of CAD models
-
M. Aubry, D. Maturana, A. A. Efros, B. C. Russell, and J. Sivic. Seeing 3D chairs: Exemplar part-based 2D-3D alignment using a large dataset of CAD models. In CVPR, 2014.
-
(2014)
CVPR
-
-
Aubry, M.1
Maturana, D.2
Efros, A.A.3
Russell, B.C.4
Sivic, J.5
-
3
-
-
84899113050
-
Painting-to-3D model alignment via discriminative visual elements
-
M. Aubry, B. C. Russell, and J. Sivic. Painting-to-3D model alignment via discriminative visual elements. ACM Transactions on Graphics, 33 (2), 2014.
-
(2014)
ACM Transactions on Graphics
, vol.33
, Issue.2
-
-
Aubry, M.1
Russell, B.C.2
Sivic, J.3
-
5
-
-
33745930513
-
On the analysis and interpretation of inhomogeneous quadratic forms as receptive fields
-
P. Berkes and L. Wiskott. On the analysis and interpretation of inhomogeneous quadratic forms as receptive fields. Neural Computation, 2006.
-
(2006)
Neural Computation
-
-
Berkes, P.1
Wiskott, L.2
-
7
-
-
84879877798
-
Invariant scattering convolution networks
-
J. Bruna and S. Mallat. Invariant scattering convolution networks. IEEE PAMI, 35 (8): 1872-1886, 2013.
-
(2013)
IEEE PAMI
, vol.35
, Issue.8
, pp. 1872-1886
-
-
Bruna, J.1
Mallat, S.2
-
10
-
-
84959184995
-
Learning to generate chairs with convolutional neural networks
-
A. Dosovitskiy, J. T. Springenberg, and T. Brox. Learning to generate chairs with convolutional neural networks. In CVPR, 2015.
-
(2015)
CVPR
-
-
Dosovitskiy, A.1
Springenberg, J.T.2
Brox, T.3
-
11
-
-
77949524387
-
-
Technical report, University of Montreal
-
D. Erhan, Y. Bengio, A. Courville, and P. Vincent. Visualizing higher-layer features of a deep network. Technical report, University of Montreal, 2009.
-
(2009)
Visualizing Higher-layer Features of A Deep Network
-
-
Erhan, D.1
Bengio, Y.2
Courville, A.3
Vincent, P.4
-
12
-
-
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
-
13
-
-
84856656486
-
Viewpoint-aware object detection and pose estimation
-
D. Glasner, M. Galun, S. Alpert, R. Basri, and G. Shakhnarovich. Viewpoint-aware object detection and pose estimation. In ICCV, 2011.
-
(2011)
ICCV
-
-
Glasner, D.1
Galun, M.2
Alpert, S.3
Basri, R.4
Shakhnarovich, G.5
-
14
-
-
33845594569
-
Dimensionality reduction by learning an invariant mapping
-
R. Hadsell, S. Chopra, and Y. LeCun. Dimensionality reduction by learning an invariant mapping. In CVPR, 2006.
-
(2006)
CVPR
-
-
Hadsell, R.1
Chopra, S.2
LeCun, Y.3
-
16
-
-
84913555165
-
-
arXiv preprint arXiv 1408 5093
-
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding. arXiv preprint arXiv: 1408. 5093, 2014.
-
(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
-
17
-
-
84919772013
-
Recognizing image style
-
S. Karayev, M. Trentacoste, H. Han, A. Agarwala, T. Darrell, A. Hertzmann, and H. Winnemöller. 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
Winnemöller, H.7
-
18
-
-
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
-
20
-
-
84455168545
-
A large-scale hierarchical multi-view RGB-D object dataset
-
K. Lai, L. Bo, X. Ren, and D. Fox. A large-scale hierarchical multi-view RGB-D object dataset. In ICRA, 2011.
-
(2011)
ICRA
-
-
Lai, K.1
Bo, L.2
Ren, X.3
Fox, D.4
-
21
-
-
0000359337
-
Backpropagation applied to handwritten zip code recognition
-
Y. LeCun, B. Boser, J. Denker, D. Henderson, R. Howard, W. Hubbard, and L. Jackel. Backpropagation applied to handwritten zip code recognition. Neural Comput., 1 (4): 541-551, 1989.
-
(1989)
Neural Comput.
, vol.1
, Issue.4
, pp. 541-551
-
-
LeCun, Y.1
Boser, B.2
Denker, J.3
Henderson, D.4
Howard, R.5
Hubbard, W.6
Jackel, L.7
-
22
-
-
5044231640
-
Learning methods for generic object recognition with invariance to pose and lighting
-
Y. LeCun, F.-J. Huang, and L. Bottou. Learning methods for generic object recognition with invariance to pose and lighting. In CVPR, 2004.
-
(2004)
CVPR
-
-
LeCun, Y.1
Huang, F.-J.2
Bottou, L.3
-
23
-
-
0042441074
-
Analyzing appearance and contour based methods for object categorization
-
IEEE
-
B. Leibe and B. Schiele. Analyzing appearance and contour based methods for object categorization. In CVPR, volume 2, pages II-409. IEEE, 2003.
-
(2003)
CVPR
, vol.2
, pp. II-409
-
-
Leibe, B.1
Schiele, B.2
-
24
-
-
84959210421
-
Understanding image representations by measuring their equivariance and equivalence
-
K. Lenc and A. Vedaldi. Understanding image representations by measuring their equivariance and equivalence. In CVPR, 2015.
-
(2015)
CVPR
-
-
Lenc, K.1
Vedaldi, A.2
-
25
-
-
84959213675
-
Understanding deep image representations by inverting them
-
A. Mahendran and A. Vedaldi. Understanding deep image representations by inverting them. In CVPR, 2015.
-
(2015)
CVPR
-
-
Mahendran, A.1
Vedaldi, A.2
-
26
-
-
0000325341
-
On lines and planes of closest fit to systems of points in space
-
K. Pearson. On lines and planes of closest fit to systems of points in space. Philosophical Magazine, 2 (11): 559-572, 1901.
-
(1901)
Philosophical Magazine
, vol.2
, Issue.11
, pp. 559-572
-
-
Pearson, K.1
-
28
-
-
84919832734
-
Learning to disentangle factors of variation with manifold interaction
-
S. Reed, K. Sohn, Y. Zhang, and H. Lee. Learning to disentangle factors of variation with manifold interaction. In ICML, 2014.
-
(2014)
ICML
-
-
Reed, S.1
Sohn, K.2
Zhang, Y.3
Lee, H.4
-
29
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
S. Roweis and L. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290 (5500): 2323-2326, 2000.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2323-2326
-
-
Roweis, S.1
Saul, L.2
-
30
-
-
84909978410
-
-
arXiv 1409 0575
-
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. 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
Berg, A.C.11
Fei-Fei, L.12
-
31
-
-
0015231889
-
Mental rotation of three dimensional objects
-
R. Shepard and J. Metzler. Mental rotation of three dimensional objects. Science, 171 (972): 701-3, 1971.
-
(1971)
Science
, vol.171
, Issue.972
, pp. 701-703
-
-
Shepard, R.1
Metzler, J.2
-
32
-
-
85083953896
-
Deep inside convolutional networks: Visualising image classification models and saliency maps
-
K. Simonyan, A. Vedaldi, and A. Zisserman. Deep inside convolutional networks: Visualising image classification models and saliency maps. In ICLR workshop, 2014.
-
(2014)
ICLR Workshop
-
-
Simonyan, K.1
Vedaldi, A.2
Zisserman, A.3
-
33
-
-
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
-
34
-
-
0027422152
-
Neuronal mechanisms of object recognition
-
K. Tanaka. Neuronal mechanisms of object recognition. Science, 262 (5134): 685-688, 1993.
-
(1993)
Science
, vol.262
, Issue.5134
, pp. 685-688
-
-
Tanaka, K.1
-
35
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
December
-
J. Tenenbaum, V. de Silva, and J. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290 (550): 2319-2323, December 2000.
-
(2000)
Science
, vol.290
, Issue.550
, pp. 2319-2323
-
-
Tenenbaum, J.1
De Silva, V.2
Langford, J.3
-
38
-
-
84949636429
-
3D ShapeNets: A deep representation for volumetric shape modeling
-
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao. 3D ShapeNets: A deep representation for volumetric shape modeling. In CVPR, 2015.
-
(2015)
CVPR
-
-
Wu, Z.1
Song, S.2
Khosla, A.3
Yu, F.4
Zhang, L.5
Tang, X.6
Xiao, J.7
-
39
-
-
84904687911
-
Beyond PASCAL: A benchmark for 3D object detection in the wild
-
Y. Xiang, R. Mottaghi, and S. Savarese. Beyond PASCAL: A benchmark for 3D object detection in the wild. In WACV, 2014.
-
(2014)
WACV
-
-
Xiang, Y.1
Mottaghi, R.2
Savarese, S.3
-
40
-
-
84937508363
-
How transferable are features in deep neural networks?
-
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson. How transferable are features in deep neural networks? In NIPS, 2014.
-
(2014)
NIPS
-
-
Yosinski, J.1
Clune, J.2
Bengio, Y.3
Lipson, H.4
-
41
-
-
84966582502
-
Visualizing and understanding convolutional networks
-
M. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. In ECCV, 2014.
-
(2014)
ECCV
-
-
Zeiler, M.1
Fergus, R.2
-
42
-
-
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. In ICLR, 2015.
-
(2015)
ICLR
-
-
Zhou, B.1
Khosla, A.2
Lapedriza, A.3
Oliva, A.4
Torralba, A.5
-
43
-
-
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
|