-
2
-
-
27844439373
-
A framework for learning predictive structures from multiple tasks and unlabeled data
-
Nov
-
R. K. Ando and T. Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6(Nov):1817-1853, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 1817-1853
-
-
Ando, R.K.1
Zhang, T.2
-
9
-
-
85041900982
-
Adversarially learned inference
-
V. Dumoulin, I. Belghazi, B. Poole, A. Lamb, M. Arjovsky, O. Mastropietro, and A. Courville. Adversarially learned inference. ICLR, 2017.
-
(2017)
ICLR
-
-
Dumoulin, V.1
Belghazi, I.2
Poole, B.3
Lamb, A.4
Arjovsky, M.5
Mastropietro, O.6
Courville, A.7
-
10
-
-
84973897611
-
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
-
D. Eigen and R. Fergus. Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture. In Proceedings of the IEEE International Conference on Computer Vision, pages 2650-2658, 2015.
-
(2015)
Proceedings of The IEEE International Conference on Computer Vision
, pp. 2650-2658
-
-
Eigen, D.1
Fergus, R.2
-
11
-
-
77951298115
-
The pascal visual object classes (voc) challenge
-
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. International journal of computer vision, 88(2):303-338, 2010.
-
(2010)
International Journal of Computer Vision
, vol.88
, Issue.2
, pp. 303-338
-
-
Everingham, M.1
Van Gool, L.2
Williams, C.K.3
Winn, J.4
Zisserman, A.5
-
15
-
-
84937849144
-
Generative adversarial nets
-
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio. Generative adversarial nets. In Advances in Neural Information Processing Systems, pages 2672-2680, 2014.
-
(2014)
Advances in Neural Information Processing Systems
, pp. 2672-2680
-
-
Goodfellow, I.1
Pouget-Abadie, J.2
Mirza, M.3
Xu, B.4
Warde-Farley, D.5
Ozair, S.6
Courville, A.7
Bengio, Y.8
-
16
-
-
84906344142
-
Learning rich features from rgb-d images for object detection and segmentation
-
Springer
-
S. Gupta, R. Girshick, P. Arbeláez, and J. Malik. Learning rich features from rgb-d images for object detection and segmentation. In European Conference on Computer Vision, pages 345-360. Springer, 2014.
-
(2014)
European Conference on Computer Vision
, pp. 345-360
-
-
Gupta, S.1
Girshick, R.2
Arbeláez, P.3
Malik, J.4
-
18
-
-
84986274465
-
Deep residual learning for image recognition
-
K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. CVPR, 2016.
-
(2016)
CVPR
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
19
-
-
33746600649
-
Reducing the dimensionality of data with neural networks
-
G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
-
(2006)
Science
, vol.313
, Issue.5786
, pp. 504-507
-
-
Hinton, G.E.1
Salakhutdinov, R.R.2
-
20
-
-
84980049328
-
Let there be Color!: Joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
-
S. Iizuka, E. Simo-Serra, and H. Ishikawa. Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification. ACM Transactions on Graphics (Proc. of SIGGRAPH 2016), 35(4), 2016.
-
(2016)
ACM Transactions on Graphics (Proc. of SIGGRAPH 2016)
, vol.35
, Issue.4
-
-
Iizuka, S.1
Simo-Serra, E.2
Ishikawa, H.3
-
21
-
-
84990069535
-
Learning visual groups from co-occurrences in space and time
-
P. Isola, D. Zoran, D. Krishnan, and E. H. Adelson. Learning visual groups from co-occurrences in space and time. International Conference on Learning Representations, Workshop, 2016.
-
(2016)
International Conference on Learning Representations, Workshop
-
-
Isola, P.1
Zoran, D.2
Krishnan, D.3
Adelson, E.H.4
-
27
-
-
85041897195
-
Colorization as a proxy task for visual understanding
-
G. Larsson, M. Maire, and G. Shakhnarovich. Colorization as a proxy task for visual understanding. CVPR, 2017.
-
(2017)
CVPR
-
-
Larsson, G.1
Maire, M.2
Shakhnarovich, G.3
-
29
-
-
84990036780
-
Shuffle and learn: Unsupervised learning using temporal order verification
-
Springer
-
I. Misra, C. L. Zitnick, and M. Hebert. Shuffle and learn: unsupervised learning using temporal order verification. In European Conference on Computer Vision, pages 527-544. Springer, 2016.
-
(2016)
European Conference on Computer Vision
, pp. 527-544
-
-
Misra, I.1
Zitnick, C.L.2
Hebert, M.3
-
31
-
-
85018873682
-
Conditional image generation with pixelcnn decoders
-
A.V. D. Oord, N. Kalchbrenner, O. Vinyals, L. Espeholt, A. Graves, and K. Kavukcuoglu. Conditional image generation with pixelcnn decoders. NIPS, 2016.
-
(2016)
NIPS
-
-
Oord, A.V.D.1
Kalchbrenner, N.2
Vinyals, O.3
Espeholt, L.4
Graves, A.5
Kavukcuoglu, K.6
-
32
-
-
84990069019
-
Ambient sound provides supervision for visual learning
-
A. Owens, J. Wu, J. H. McDermott, W. T. Freeman, and A. Torralba. Ambient sound provides supervision for visual learning. In ECCV, 2016.
-
(2016)
ECCV
-
-
Owens, A.1
Wu, J.2
McDermott, J.H.3
Freeman, W.T.4
Torralba, A.5
-
33
-
-
85041908735
-
Learning features by watching objects move
-
D. Pathak, R. Girshick, P. Dollár, T. Darrell, and B. Hariha-ran. Learning features by watching objects move. CVPR, 2017.
-
(2017)
CVPR
-
-
Pathak, D.1
Girshick, R.2
Dollár, P.3
Darrell, T.4
Hariha-Ran, B.5
-
34
-
-
84986294165
-
Context encoders: Feature learning by inpainting
-
D. Pathak, P. Krähenbühl, J. Donahue, T. Darrell, and A. Efros. Context encoders: Feature learning by inpainting. In CVPR, 2016.
-
(2016)
CVPR
-
-
Pathak, D.1
Krähenbühl, P.2
Donahue, J.3
Darrell, T.4
Efros, A.5
-
35
-
-
34547679821
-
Visual equivalence: Towards a new standard for image fidelity
-
G. Ramanarayanan, J. Ferwerda, B. Walter, and K. Bala. Visual equivalence: towards a new standard for image fidelity. ACM Transactions on Graphics (TOG), 26(3):76, 2007.
-
(2007)
ACM Transactions on Graphics (TOG)
, vol.26
, Issue.3
, pp. 76
-
-
Ramanarayanan, G.1
Ferwerda, J.2
Walter, B.3
Bala, K.4
-
36
-
-
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. International Journal of Computer Vision, 115(3):211-252, 2015.
-
(2015)
International Journal of Computer Vision
, 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
-
37
-
-
73249147662
-
Deep boltzmann machines
-
R. Salakhutdinov and G. E. Hinton. Deep boltzmann machines. In AISTATS, volume 1, page 3, 2009.
-
(2009)
AISTATS
, vol.1
, pp. 3
-
-
Salakhutdinov, R.1
Hinton, G.E.2
-
38
-
-
84867713871
-
Indoor segmentation and support inference from rgbd images
-
Springer
-
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus. Indoor segmentation and support inference from rgbd images. In European Conference on Computer Vision, pages 746-760. Springer, 2012.
-
(2012)
European Conference on Computer Vision
, pp. 746-760
-
-
Silberman, N.1
Hoiem, D.2
Kohli, P.3
Fergus, R.4
-
40
-
-
0000329993
-
Information processing in dynamical systems: Foundations of harmony theory
-
DTIC Document
-
P. Smolensky. Information processing in dynamical systems: Foundations of harmony theory. Technical report, DTIC Document, 1986.
-
(1986)
Technical Report
-
-
Smolensky, P.1
-
43
-
-
56449089103
-
Extracting and composing robust features with denoising autoencoders
-
ACM
-
P. Vincent, H. Larochelle, Y. Bengio, and P.-A. Manzagol. Extracting and composing robust features with denoising autoencoders. In Proceedings of the 25th international conference on Machine learning, pages 1096-1103. ACM, 2008.
-
(2008)
Proceedings of The 25th International Conference on Machine Learning
, pp. 1096-1103
-
-
Vincent, P.1
Larochelle, H.2
Bengio, Y.3
Manzagol, P.-A.4
-
48
-
-
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, pages 487-495, 2014.
-
(2014)
Advances in Neural Information Processing Systems
, pp. 487-495
-
-
Zhou, B.1
Lapedriza, A.2
Xiao, J.3
Torralba, A.4
Oliva, A.5
|