-
1
-
-
80053551322
-
Building Rome in a day
-
S. Agarwal, Y. Furukawa, N. Snavely, I. Simon, B. Curless, S. M. Seitz, and R. Szeliski. Building Rome in a day. Communications of the ACM, 2011. 2
-
(2011)
Communications of the ACM
, vol.2
-
-
Agarwal, S.1
Furukawa, Y.2
Snavely, N.3
Simon, I.4
Curless, B.5
Seitz, S.M.6
Szeliski, R.7
-
3
-
-
84906490449
-
Neural codes for image retrieval
-
1, 2, 3, 8
-
A. Babenko, A. Slesarev, A. Chigorin, and V. Lempitsky. Neural codes for image retrieval. In ECCV, 2014. 1, 2, 3, 8
-
(2014)
ECCV
-
-
Babenko, A.1
Slesarev, A.2
Chigorin, A.3
Lempitsky, V.4
-
4
-
-
80052882128
-
Object recognition with hierarchical kernel descriptors
-
L. Bo, K. Lai, X. Ren, and D. Fox. Object recognition with hierarchical kernel descriptors. In CVPR, 2011. 5
-
(2011)
CVPR
, vol.5
-
-
Bo, L.1
Lai, K.2
Ren, X.3
Fox, D.4
-
5
-
-
85162018819
-
Kernel descriptors for visual recognition
-
L. Bo, X. Ren, and D. Fox. Kernel descriptors for visual recognition. In NIPS, 2010. 2, 5
-
(2010)
NIPS
, vol.2
, pp. 5
-
-
Bo, L.1
Ren, X.2
Fox, D.3
-
7
-
-
78649324041
-
Discriminative learning of local image descriptors
-
M. Brown, G. Hua, and S. Winder. Discriminative learning of local image descriptors. PAMI, 2011. 2
-
(2011)
PAMI
, vol.2
-
-
Brown, M.1
Hua, G.2
Winder, S.3
-
8
-
-
79952521625
-
BRIEF: Binary robust independent elementary features
-
M. Calonder, V. Lepetit, C. Strecha, and P. Fua. BRIEF: Binary robust independent elementary features. In ECCV, 2010. 2
-
(2010)
ECCV
, vol.2
-
-
Calonder, M.1
Lepetit, V.2
Strecha, C.3
Fua, P.4
-
9
-
-
85198028989
-
ImageNet: A large-scale hierarchical image database
-
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A large-scale hierarchical image database. In CVPR, 2009. 3
-
(2009)
CVPR
, vol.3
-
-
Deng, J.1
Dong, W.2
Socher, R.3
Li, L.-J.4
Li, K.5
Fei-Fei, L.6
-
10
-
-
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. In ICML, 2014. 1
-
(2014)
ICML
, vol.1
-
-
Donahue, J.1
Jia, Y.2
Vinyals, O.3
Hoffman, J.4
Zhang, N.5
Tzeng, E.6
Darrell, T.7
-
11
-
-
85067215717
-
Discriminative unsupervised feature learning with convolutional neural networks
-
A. Dosovitskiy, J. T. Springenberg, M. Riedmiller, and T. Brox. Discriminative unsupervised feature learning with convolutional neural networks. NIPS, 2014. 2, 4
-
(2014)
NIPS
, vol.2
, pp. 4
-
-
Dosovitskiy, A.1
Springenberg, J.T.2
Riedmiller, M.3
Brox, T.4
-
12
-
-
84921339610
-
-
arXiv Preprint. 1, 3, 4, 6, 7
-
P. Fischer, A. Dosovitskiy, and T. Brox. Descriptor matching with convolutional neural networks: A comparison to SIFT. ArXiv Preprint, 2014. 1, 3, 4, 6, 7
-
(2014)
Descriptor Matching with Convolutional Neural Networks: A Comparison to SIFT
-
-
Fischer, P.1
Dosovitskiy, A.2
Brox, T.3
-
13
-
-
84911400494
-
Rich feature hierarchies for accurate object detection and semantic segmentation
-
1, 2
-
R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014. 1, 2
-
(2014)
CVPR
-
-
Girshick, R.1
Donahue, J.2
Darrell, T.3
Malik, J.4
-
14
-
-
84938217896
-
Multi-scale orderless pooling of deep convolutional activation features
-
Y. Gong, L. Wang, R. Guo, and S. Lazebnik. Multi-scale orderless pooling of deep convolutional activation features. In ECCV, 2014. 3, 8
-
(2014)
ECCV
, vol.3
, pp. 8
-
-
Gong, Y.1
Wang, L.2
Guo, R.3
Lazebnik, S.4
-
15
-
-
84877623414
-
Negative evidences and cooccurrences in image retrieval: The benefit of PCA and whitening
-
H. Jégou and O. Chum. Negative evidences and cooccurrences in image retrieval: The benefit of PCA and whitening. In ECCV, 2012. 8
-
(2012)
ECCV
, vol.8
-
-
Jégou, H.1
Chum, O.2
-
16
-
-
70449560133
-
Hamming embedding and weak geometric consistency for large scale image search
-
H. Jegou, M. Douze, and C. Schmid. Hamming embedding and weak geometric consistency for large scale image search. In ECCV. 2008. 2
-
(2008)
ECCV
, vol.2
-
-
Jegou, H.1
Douze, M.2
Schmid, C.3
-
17
-
-
84875881757
-
Product quantization for nearest neighbor search
-
H. Jegou, M. Douze, and C. Schmid. Product quantization for nearest neighbor search. PAMI, 2011. 6, 8
-
(2011)
PAMI
, vol.6
, pp. 8
-
-
Jegou, H.1
Douze, M.2
Schmid, C.3
-
18
-
-
77956004473
-
Aggregating local descriptors into a compact image representation
-
H. Jégou, M. Douze, C. Schmid, and P. Pérez. Aggregating local descriptors into a compact image representation. In CVPR, 2010. 3
-
(2010)
CVPR
, vol.3
-
-
Jégou, H.1
Douze, M.2
Schmid, C.3
Pérez, P.4
-
19
-
-
84874556652
-
Aggregating local image descriptors into compact codes
-
H. Jégou, F. Perronnin, M. Douze, J. Sánchez, P. Pérez, and C. Schmid. Aggregating local image descriptors into compact codes. PAMI, 2012. 1, 8
-
(2012)
PAMI
, vol.1
, pp. 8
-
-
Jégou, H.1
Perronnin, F.2
Douze, M.3
Sánchez, J.4
Pérez, P.5
Schmid, C.6
-
20
-
-
84973928606
-
-
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. 6
-
(2014)
Caffe: Convolutional Architecture for Fast Feature Embedding
, vol.6
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.6
Guadarrama, S.7
Darrell, T.8
-
21
-
-
84911376543
-
Learning fine-grained image similarity with deep ranking
-
J. Jiang, Y. Song, T. Leung, C. Rosenberg, J. Wang, J. Philbin, B. Chen, and Y. Wu. Learning fine-grained image similarity with deep ranking. In CVPR, 2014. 3
-
(2014)
CVPR
, vol.3
-
-
Jiang, J.1
Song, Y.2
Leung, T.3
Rosenberg, C.4
Wang, J.5
Philbin, J.6
Chen, B.7
Wu, Y.8
-
22
-
-
84876231242
-
ImageNet classification with deep convolutional neural networks
-
1, 3, 4
-
A. Krizhevsky, I. Sutskever, and G. Hinton. ImageNet classification with deep convolutional neural networks. In NIPS, 2012. 1, 3, 4
-
(2012)
NIPS
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.3
-
23
-
-
0000494467
-
Handwritten digit recognition with a back-propagation network
-
Y. LeCun, B. Boser, J. Denker, D. Henderson, R. Howard, W. Hubbard, and L. Jackel. Handwritten digit recognition with a back-propagation network. NIPS, 1989. 1
-
(1989)
NIPS
, vol.1
-
-
LeCun, Y.1
Boser, B.2
Denker, J.3
Henderson, D.4
Howard, R.5
Hubbard, W.6
Jackel, L.7
-
24
-
-
84856654969
-
Location recognition using prioritized feature matching
-
Y. Li, N. Snavely, and D. P. Huttenlocher. Location recognition using prioritized feature matching. In ECCV. 2010. 6
-
(2010)
ECCV
, vol.6
-
-
Li, Y.1
Snavely, N.2
Huttenlocher, D.P.3
-
25
-
-
84959224983
-
Do Convnets learn correspondances
-
1, 2, 3
-
J. Long, N. Zhang, and T. Darrell. Do Convnets learn correspondances In NIPS, 2014. 1, 2, 3
-
(2014)
NIPS
-
-
Long, J.1
Zhang, N.2
Darrell, T.3
-
26
-
-
3042535216
-
Distinctive image features from scale-invariant keypoints
-
1, 2, 3
-
D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004. 1, 2, 3
-
(2004)
IJCV
-
-
Lowe, D.G.1
-
27
-
-
84937908307
-
Convolutional kernel networks
-
2, 3, 4, 5, 7
-
J. Mairal, P. Koniusz, Z. Harchaoui, and C. Schmid. Convolutional kernel networks. In NIPS, 2014. 2, 3, 4, 5, 7
-
(2014)
NIPS
-
-
Mairal, J.1
Koniusz, P.2
Harchaoui, Z.3
Schmid, C.4
-
28
-
-
9644260534
-
Scale & affine invariant interest point detectors
-
K. Mikolajczyk and C. Schmid. Scale & affine invariant interest point detectors. IJCV, 2004. 3
-
(2004)
IJCV
, vol.3
-
-
Mikolajczyk, K.1
Schmid, C.2
-
29
-
-
27644547620
-
A performance evaluation of local descriptors
-
2, 5
-
K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. PAMI, 2005. 2, 5
-
(2005)
PAMI
-
-
Mikolajczyk, K.1
Schmid, C.2
-
30
-
-
33244468369
-
A comparison of affine region detectors
-
1, 3
-
K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool. A comparison of affine region detectors. IJCV, 2005. 1, 3
-
(2005)
IJCV
-
-
Mikolajczyk, K.1
Tuytelaars, T.2
Schmid, C.3
Zisserman, A.4
Matas, J.5
Schaffalitzky, F.6
Kadir, T.7
Van Gool, L.8
-
31
-
-
84911449395
-
Learning and transferring mid-level image representations using convolutional neural networks
-
1, 2
-
M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Learning and transferring mid-level image representations using convolutional neural networks. In CVPR, 2014. 1, 2
-
(2014)
CVPR
-
-
Oquab, M.1
Bottou, L.2
Laptev, I.3
Sivic, J.4
-
32
-
-
70450179951
-
Efficient representation of local geometry for large scale object retrieval
-
M. Perdoch, O. Chum, and J. Matas. Efficient representation of local geometry for large scale object retrieval. In CVPR, 2009. 8
-
(2009)
CVPR
, vol.8
-
-
Perdoch, M.1
Chum, O.2
Matas, J.3
-
33
-
-
34948815101
-
Fisher kernels on visual vocabularies for image categorization
-
F. Perronnin and C. Dance. Fisher kernels on visual vocabularies for image categorization. In CVPR, 2007. 2
-
(2007)
CVPR
, vol.2
-
-
Perronnin, F.1
Dance, C.2
-
34
-
-
77956008923
-
Large-scale image categorization with explicit data embedding
-
2, 4
-
F. Perronnin, J. Sánchez, and Y. Liu. Large-scale image categorization with explicit data embedding. In CVPR, 2010. 2, 4
-
(2010)
CVPR
-
-
Perronnin, F.1
Sánchez, J.2
Liu, Y.3
-
35
-
-
34948903793
-
Object retrieval with large vocabularies and fast spatial matching
-
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. In CVPR, 2007. 6
-
(2007)
CVPR
, vol.6
-
-
Philbin, J.1
Chum, O.2
Isard, M.3
Sivic, J.4
Zisserman, A.5
-
36
-
-
51949105132
-
Lost in quantization: Improving particular object retrieval in large scale image databases
-
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Lost in quantization: Improving particular object retrieval in large scale image databases. In CVPR, 2008. 8
-
(2008)
CVPR
, vol.8
-
-
Philbin, J.1
Chum, O.2
Isard, M.3
Sivic, J.4
Zisserman, A.5
-
39
-
-
84941247315
-
-
arXiv preprint, 1, 3
-
E. Simo-Serra, E. Trulls, L. Ferraz, I. Kokkinos, and F. Moreno-Noguer. Fracking deep convolutional image descriptors. Arxiv preprint, 2015. 1, 3
-
(2015)
Fracking Deep Convolutional Image Descriptors
-
-
Simo-Serra, E.1
Trulls, E.2
Ferraz, L.3
Kokkinos, I.4
Moreno-Noguer, F.5
-
40
-
-
84911454787
-
Learning local feature descriptors using convex optimisation
-
K. Simonyan, A. Vedaldi, and A. Zisserman. Learning local feature descriptors using convex optimisation. PAMI, 2014. 2
-
(2014)
PAMI
, vol.2
-
-
Simonyan, K.1
Vedaldi, A.2
Zisserman, A.3
-
41
-
-
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. 1
-
(2003)
ICCV
, vol.1
-
-
Sivic, J.1
Zisserman, A.2
-
42
-
-
77949875753
-
Daisy: An efficient dense descriptor applied to wide-baseline stereo
-
E. Tola, V. Lepetit, and P. Fua. Daisy: An efficient dense descriptor applied to wide-baseline stereo. PAMI, 2010. 2
-
(2010)
PAMI
, vol.2
-
-
Tola, E.1
Lepetit, V.2
Fua, P.3
-
44
-
-
84856194352
-
Efficient additive kernels via explicit feature maps
-
2, 4
-
A. Vedaldi and A. Zisserman. Efficient additive kernels via explicit feature maps. TPAMI, 2012. 2, 4
-
(2012)
TPAMI
-
-
Vedaldi, A.1
Zisserman, A.2
-
45
-
-
84863054049
-
Local intensity order pattern for feature description
-
Z. Wang, B. Fan, and F. Wu. Local intensity order pattern for feature description. In ICCV, 2011. 2
-
(2011)
ICCV
, vol.2
-
-
Wang, Z.1
Fan, B.2
Wu, F.3
-
46
-
-
70450208928
-
Picking the best daisy
-
2, 3, 6
-
S. Winder, G. Hua, and M. Brown. Picking the best daisy. In CVPR, 2009. 2, 3, 6
-
(2009)
CVPR
-
-
Winder, S.1
Hua, G.2
Brown, M.3
-
47
-
-
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. 2
-
(2014)
NIPS
, vol.2
-
-
Yosinski, J.1
Clune, J.2
Bengio, Y.3
Lipson, H.4
|