-
1
-
-
85044546226
-
-
Accessed, 2017-04-21. 8
-
Bertrand gondouin. https://twitter.com/bgondouin/status/818571935529377792. Accessed, 2017-04-21. 8
-
Bertrand Gondouin
-
-
-
2
-
-
85044525485
-
-
Brannon dorsey. Accessed, 2017-04-21. 8
-
Brannon dorsey. https://twitter.com/brannondorsey/status/806283494041223168. Accessed, 2017-04-21. 8
-
-
-
-
3
-
-
85044503615
-
-
Accessed: 2017-04-21. 8
-
Christopher hesse. https://affinelayer.com/pixsrv/. Accessed: 2017-04-21. 8
-
Christopher Hesse
-
-
-
4
-
-
85044507568
-
-
Accessed: 2017-04-21. 8
-
Jack qiao. http://colormind.io/blog/. Accessed: 2017-04-21. 8
-
Jack Qiao
-
-
-
5
-
-
85044535369
-
-
Accessed, 2017-04-21. 8
-
Jasper van loenen. https://jaspervanloenen.com/neural-city/. Accessed, 2017-04-21. 8
-
Jasper Van Loenen
-
-
-
6
-
-
85044510079
-
-
Accessed, 2017-04-21. 8
-
Kaihu chen. http://www.terraai.org/imageops/index.html. Accessed, 2017-04-21. 8
-
Kaihu Chen
-
-
-
7
-
-
85044532331
-
-
Accessed, 2017-04-21. 8
-
Mario klingemann. https://twitter.com/quasimondo/status/826065030944870400. Accessed, 2017-04-21. 8
-
Mario Klingemann
-
-
-
8
-
-
24644478715
-
A non-local algorithm for image denoising
-
In IEEE, 1
-
A. Buades, B. Coll, and J.-M. Morel. A non-local algorithm for image denoising. In CVPR, volume 2, pages 60-65. IEEE, 2005. 1
-
(2005)
CVPR
, vol.2
, pp. 60-65
-
-
Buades, A.1
Coll, B.2
Morel, J.-M.3
-
9
-
-
85083954148
-
Semantic image segmentation with deep convolutional nets and fully connected crfs
-
In 2
-
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. Semantic image segmentation with deep convolutional nets and fully connected crfs. In ICLR, 2015. 2
-
(2015)
ICLR
-
-
Chen, L.-C.1
Papandreou, G.2
Kokkinos, I.3
Murphy, K.4
Yuille, A.L.5
-
10
-
-
85024284027
-
Sketch2photo: Internet image montage
-
1
-
T. Chen, M.-M. Cheng, P. Tan, A. Shamir, and S.-M. Hu. Sketch2photo: internet image montage. ACM Transactions on Graphics (TOG), 28(5):124, 2009. 1
-
(2009)
ACM Transactions on Graphics (TOG)
, vol.28
, Issue.5
, pp. 124
-
-
Chen, T.1
Cheng, M.-M.2
Tan, P.3
Shamir, A.4
Hu, S.-M.5
-
11
-
-
84986255616
-
The cityscapes dataset for semantic urban scene understanding
-
In 4
-
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. The cityscapes dataset for semantic urban scene understanding. In CVPR), 2016. 4
-
(2016)
CVPR)
-
-
Cordts, M.1
Omran, M.2
Ramos, S.3
Rehfeld, T.4
Enzweiler, M.5
Benenson, R.6
Franke, U.7
Roth, S.8
Schiele, B.9
-
12
-
-
84965143571
-
Deep generative image models using alaplacian pyramid of adversarial networks
-
2
-
E. L. Denton, S. Chintala, R. Fergus, et al. Deep generative image models using alaplacian pyramid of adversarial networks. In NIPS, pages 1486-1494, 2015. 2
-
(2015)
NIPS
, pp. 1486-1494
-
-
Denton, E.L.1
Chintala, S.2
Fergus, R.3
-
14
-
-
0035148826
-
Image quilting for texture synthesis and transfer
-
In ACM, 1, 4
-
A. A. Efros and W. T. Freeman. Image quilting for texture synthesis and transfer. In SIGGRAPH, pages 341-346. ACM, 2001. 1, 4
-
(2001)
SIGGRAPH
, pp. 341-346
-
-
Efros, A.A.1
Freeman, W.T.2
-
15
-
-
0033285309
-
Texture synthesis by nonparametric sampling
-
In IEEE, 4
-
A. A. Efros and T. K. Leung. Texture synthesis by nonparametric sampling. In ICCV, volume 2, pages 1033-1038. IEEE, 1999. 4
-
(1999)
ICCV
, vol.2
, pp. 1033-1038
-
-
Efros, A.A.1
Leung, T.K.2
-
16
-
-
84973897611
-
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
-
In 1
-
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. 1
-
(2015)
Proceedings of The IEEE International Conference on Computer Vision
, pp. 2650-2658
-
-
Eigen, D.1
Fergus, R.2
-
17
-
-
84870175866
-
How do humans sketch objects?
-
4, 8
-
M. Eitz, J. Hays, and M. Alexa. How do humans sketch objects? SIGGRAPH, 31(4):44-1, 2012. 4, 8
-
(2012)
SIGGRAPH
, vol.31
, Issue.4
, pp. 44-51
-
-
Eitz, M.1
Hays, J.2
Alexa, M.3
-
18
-
-
33749249573
-
Removing camera shake from a single photograph
-
In ACM, 1
-
R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman. Removing camera shake from a single photograph. In ACM Transactions on Graphics (TOG), volume 25, pages 787-794. ACM, 2006. 1
-
(2006)
ACM Transactions on Graphics (TOG)
, vol.25
, pp. 787-794
-
-
Fergus, R.1
Singh, B.2
Hertzmann, A.3
Roweis, S.T.4
Freeman, W.T.5
-
20
-
-
84986325538
-
Image style transfer using convolutional neural networks
-
4
-
L. A. Gatys, A. S. Ecker, and M. Bethge. Image style transfer using convolutional neural networks. CVPR, 2016. 4
-
(2016)
CVPR
-
-
Gatys, L.A.1
Ecker, A.S.2
Bethge, M.3
-
22
-
-
84937849144
-
Generative adversarial nets
-
In 2, 4, 5, 6
-
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio. Generative adversarial nets. In NIPS, 2014. 2, 4, 5, 6
-
(2014)
NIPS
-
-
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
-
23
-
-
0035148669
-
Image analogies
-
In ACM, 1, 4
-
A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin. Image analogies. In SIGGRAPH, pages 327-340. ACM, 2001. 1, 4
-
(2001)
SIGGRAPH
, pp. 327-340
-
-
Hertzmann, A.1
Jacobs, C.E.2
Oliver, N.3
Curless, B.4
Salesin, D.H.5
-
24
-
-
33746600649
-
Reducing the dimensionality of data with neural networks
-
3
-
G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006. 3
-
(2006)
Science
, vol.313
, Issue.5786
, pp. 504-507
-
-
Hinton, G.E.1
Salakhutdinov, R.R.2
-
25
-
-
84980049328
-
Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
-
2
-
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 (TOG), 35(4), 2016. 2
-
(2016)
ACM Transactions on Graphics (TOG)
, vol.35
, Issue.4
-
-
Iizuka, S.1
Simo-Serra, E.2
Ishikawa, H.3
-
29
-
-
85083951076
-
A method for stochastic optimization
-
4
-
D. Kingma and J. Ba. Adam: A method for stochastic optimization. ICLR, 2015. 4
-
(2015)
ICLR
-
-
Kingma, D.1
Adam, J.Ba.2
-
30
-
-
84905741277
-
Transient attributes for high-level understanding and editing of outdoor scenes
-
1, 4
-
P.-Y. Laffont, Z. Ren, X. Tao, C. Qian, and J. Hays. Transient attributes for high-level understanding and editing of outdoor scenes. ACM Transactions on Graphics (TOG), 33(4):149, 2014. 1, 4
-
(2014)
ACM Transactions on Graphics (TOG)
, vol.33
, Issue.4
, pp. 149
-
-
Laffont, P.-Y.1
Ren, Z.2
Tao, X.3
Qian, C.4
Hays, J.5
-
32
-
-
85030792287
-
Learning representations for automatic colorization
-
2, 7
-
G. Larsson, M. Maire, and G. Shakhnarovich. Learning representations for automatic colorization. ECCV, 2016. 2, 7
-
(2016)
ECCV
-
-
Larsson, G.1
Maire, M.2
Shakhnarovich, G.3
-
33
-
-
85019017178
-
-
arXiv preprint 2
-
C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, et al. Photo-realistic single image super-resolution using a generative adversarial network. arXiv preprint arXiv:1609.04802, 2016. 2
-
(2016)
Photo-Realistic Single Image Super-Resolution Using A Generative Adversarial Network
-
-
Ledig, C.1
Theis, L.2
Huszár, F.3
Caballero, J.4
Cunningham, A.5
Acosta, A.6
Aitken, A.7
Tejani, A.8
Totz, J.9
Wang, Z.10
-
34
-
-
84986290423
-
Combining markov random fields and convolutional neural networks for image synthesis
-
2, 4
-
C. Li and M. Wand. Combining markov random fields and convolutional neural networks for image synthesis. CVPR, 2016. 2, 4
-
(2016)
CVPR
-
-
Li, C.1
Wand, M.2
-
35
-
-
84990854650
-
Precomputed real-time texture synthesis with markovian generative adversarial networks
-
2, 4
-
C. Li and M. Wand. Precomputed real-time texture synthesis with markovian generative adversarial networks. ECCV, 2016. 2, 4
-
(2016)
ECCV
-
-
Li, C.1
Wand, M.2
-
36
-
-
84937144752
-
Fully convolutional networks for semantic segmentation
-
In 1, 2, 4
-
J. Long, E. Shelhamer, and T. Darrell. Fully convolutional networks for semantic segmentation. In CVPR, pages 3431-3440, 2015. 1, 2, 4
-
(2015)
CVPR
, pp. 3431-3440
-
-
Long, J.1
Shelhamer, E.2
Darrell, T.3
-
37
-
-
85083952137
-
Deep multi-scale video prediction beyond mean square error
-
2, 3
-
M. Mathieu, C. Couprie, and Y. LeCun. Deep multi-scale video prediction beyond mean square error. ICLR, 2016. 2, 3
-
(2016)
ICLR
-
-
Mathieu, M.1
Couprie, C.2
LeCun, Y.3
-
39
-
-
84986249782
-
Visually indicated sounds
-
In 4
-
A. Owens, P. Isola, J. McDermott, A. Torralba, E. H. Adel-son, and W. T. Freeman. Visually indicated sounds. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2405-2413, 2016. 4
-
(2016)
Proceedings of The IEEE Conference on Computer Vision and Pattern Recognition
, pp. 2405-2413
-
-
Owens, A.1
Isola, P.2
McDermott, J.3
Torralba, A.4
Adel-Son, E.H.5
Freeman, W.T.6
-
40
-
-
84986294165
-
Context encoders: Feature learning by inpainting
-
2, 3
-
D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros. Context encoders: Feature learning by inpainting. CVPR, 2016. 2, 3
-
(2016)
CVPR
-
-
Pathak, D.1
Krahenbuhl, P.2
Donahue, J.3
Darrell, T.4
Efros, A.A.5
-
42
-
-
85044520509
-
Spatial pattern templates for recognition of objects with regular structure
-
Saar-brucken, Germany, 4, 8
-
R. Š. Radim Tyleček. Spatial pattern templates for recognition of objects with regular structure. In Proc. GCPR, Saar-brucken, Germany, 2013. 4, 8
-
(2013)
Proc. GCPR
-
-
Radim Tyleček, R.Š.1
-
43
-
-
85006947809
-
-
arXiv preprint 2
-
S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee. Generative adversarial text to image synthesis. arXiv preprint arXiv:1605.05396, 2016. 2
-
(2016)
Generative Adversarial Text to Image Synthesis
-
-
Reed, S.1
Akata, Z.2
Yan, X.3
Logeswaran, L.4
Schiele, B.5
Lee, H.6
-
44
-
-
85038447381
-
Generating interpretable images with controllable structure
-
2016. 2
-
S. Reed, A. van den Oord, N. Kalchbrenner, V. Bapst, M. Botvinick, and N. de Freitas. Generating interpretable images with controllable structure. Technical report, Technical report, 2016. 2, 2016. 2
-
(2016)
Technical Report, Technical Report
, vol.2
-
-
Reed, S.1
Van Den Oord, A.2
Kalchbrenner, N.3
Bapst, V.4
Botvinick, M.5
De Freitas, N.6
-
45
-
-
85018890661
-
Learning what and where to draw
-
In 2
-
S. E. Reed, Z. Akata, S. Mohan, S. Tenka, B. Schiele, and H. Lee. Learning what and where to draw. In Advances In Neural Information Processing Systems, pages 217-225, 2016. 2
-
(2016)
Advances In Neural Information Processing Systems
, pp. 217-225
-
-
Reed, S.E.1
Akata, Z.2
Mohan, S.3
Tenka, S.4
Schiele, B.5
Lee, H.6
-
46
-
-
0035449032
-
Color transfer between images
-
6
-
E. Reinhard, M. Ashikhmin, B. Gooch, and P. Shirley. Color transfer between images. IEEE Computer Graphics and Applications, 21:34-41, 2001. 6
-
(2001)
IEEE Computer Graphics and Applications
, vol.21
, pp. 34-41
-
-
Reinhard, E.1
Ashikhmin, M.2
Gooch, B.3
Shirley, P.4
-
47
-
-
84951834022
-
U-net: Convolutional networks for biomedical image segmentation
-
In Springer, 2, 3
-
O. Ronneberger, P. Fischer, and T. Brox. U-net: Convolutional networks for biomedical image segmentation. In MIC-CAI, pages 234-241. Springer, 2015. 2, 3
-
(2015)
MIC-CAI
, pp. 234-241
-
-
Ronneberger, O.1
Fischer, P.2
Brox, T.3
-
48
-
-
84947041871
-
Imagenet large scale visual recognition challenge
-
4, 7
-
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. 4, 7
-
(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
-
49
-
-
84989923527
-
-
arXiv preprint 2, 4
-
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen. Improved techniques for training gans. arXiv preprint arXiv:1606.03498, 2016. 2, 4
-
(2016)
Improved Techniques for Training Gans
-
-
Salimans, T.1
Goodfellow, I.2
Zaremba, W.3
Cheung, V.4
Radford, A.5
Chen, X.6
-
50
-
-
84887839353
-
Data-driven hallucination of different times of day from a single outdoor photo
-
1
-
Y. Shih, S. Paris, F. Durand, and W. T. Freeman. Data-driven hallucination of different times of day from a single outdoor photo. ACM Transactions on Graphics (TOG), 32(6):200, 2013. 1
-
(2013)
ACM Transactions on Graphics (TOG)
, vol.32
, Issue.6
, pp. 200
-
-
Shih, Y.1
Paris, S.2
Durand, F.3
Freeman, W.T.4
-
52
-
-
84990022453
-
Generative image modeling using style and structure adversarial networks
-
2, 3, 4
-
X. Wang and A. Gupta. Generative image modeling using style and structure adversarial networks. ECCV, 2016. 2, 3, 4
-
(2016)
ECCV
-
-
Wang, X.1
Gupta, A.2
-
53
-
-
1942436689
-
Image quality assessment: From error visibility to structural similarity
-
2
-
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600-612, 2004. 2
-
(2004)
IEEE Transactions on Image Processing
, vol.13
, Issue.4
, pp. 600-612
-
-
Wang, Z.1
Bovik, A.C.2
Sheikh, H.R.3
Simoncelli, E.P.4
-
55
-
-
84973859794
-
Holistically-nested edge detection
-
In 1, 2, 4
-
S. Xie and Z. Tu. Holistically-nested edge detection. In ICCV, 2015. 1, 2, 4
-
(2015)
ICCV
-
-
Xie, S.1
Tu, Z.2
-
56
-
-
85008684527
-
Pixel-level domain transfer
-
2, 3
-
D. Yoo, N. Kim, S. Park, A. S. Paek, and I. S. Kweon. Pixel-level domain transfer. ECCV, 2016. 2, 3
-
(2016)
ECCV
-
-
Yoo, D.1
Kim, N.2
Park, S.3
Paek, A.S.4
Kweon, I.S.5
-
57
-
-
84911374908
-
Fine-Grained Visual Comparisons with Local Learning
-
In 4
-
A. Yu and K. Grauman. Fine-Grained Visual Comparisons with Local Learning. In CVPR, 2014. 4
-
(2014)
CVPR
-
-
Yu, A.1
Grauman, K.2
-
58
-
-
84990021580
-
Colorful image colorization
-
1, 2, 4, 7
-
R. Zhang, P. Isola, and A. A. Efros. Colorful image colorization. ECCV, 2016. 1, 2, 4, 7
-
(2016)
ECCV
-
-
Zhang, R.1
Isola, P.2
Efros, A.A.3
-
60
-
-
85019205829
-
Learning temporal transformations from time-lapse videos
-
In 2, 3, 7
-
Y. Zhou and T. L. Berg. Learning temporal transformations from time-lapse videos. In ECCV, 2016. 2, 3, 7
-
(2016)
ECCV
-
-
Zhou, Y.1
Berg, T.L.2
-
61
-
-
85030465393
-
Generative visual manipulation on the natural image manifold
-
In 2, 4
-
J.-Y. Zhu, P. Krähenbühl, E. Shechtman, and A. A. Efros. Generative visual manipulation on the natural image manifold. In ECCV, 2016. 2, 4
-
(2016)
ECCV
-
-
Zhu, J.-Y.1
Krähenbühl, P.2
Shechtman, E.3
Efros, A.A.4
|