F. Durand, An invitation to discuss computer depiction, Proceedings of the second international symposium on Non-photorealistic animation and rendering , NPAR '02, pp.111-124, 2002.
DOI : 10.1145/508530.508550
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.2793

J. Kyprianidis, J. Collomosse, T. Wang, and T. Isenberg, State of the art: A taxonomy of artistic stylization techniques for images and video, IEEE TVCG, vol.19, issue.5, pp.866-885, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00781502

L. A. Gatys, A. S. Ecker, and M. Bethge, A Neural Algorithm of Artistic Style, Journal of Vision, vol.16, issue.12
DOI : 10.1167/16.12.326

C. Li and M. Wand, Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks, European Conference on Computer Vision, pp.702-716, 2016.
DOI : 10.1007/978-3-319-10590-1_53
URL : http://arxiv.org/abs/1604.04382

V. Dumoulin, J. Shlens, and M. Kudlur, A learned representation for artistic style, ICLR, 2017.

O. Frigo, N. Sabater, J. Delon, and P. Hellier, Split and Match: Example-Based Adaptive Patch Sampling for Unsupervised Style Transfer, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
DOI : 10.1109/CVPR.2016.66
URL : https://hal.archives-ouvertes.fr/hal-01280818

A. A. Efros and W. T. Freeman, Image quilting for texture synthesis and transfer, Proceedings of the 28th annual conference on Computer graphics and interactive techniques , SIGGRAPH '01, pp.341-346, 2001.
DOI : 10.1145/383259.383296
URL : http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.18.9703&rep=rep1&type=pdf

A. Criminisi, P. Perez, and K. Toyama, Region Filling and Object Removal by Exemplar-Based Image Inpainting, IEEE Transactions on Image Processing, vol.13, issue.9, pp.1200-1212, 2004.
DOI : 10.1109/TIP.2004.833105
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.9434

W. Freeman, T. Jones, and E. Pasztor, Example-based super-resolution, IEEE Computer Graphics and Applications, vol.22, issue.2, pp.56-65, 2002.
DOI : 10.1109/38.988747

A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin, Image analogies, Proceedings of the 28th annual conference on Computer graphics and interactive techniques , SIGGRAPH '01, pp.327-340, 2001.
DOI : 10.1145/383259.383295

E. Reinhard, M. Ashikhmin, B. Gooch, and P. Shirley, Color transfer between images, IEEE Computer Graphics and Applications, vol.21, issue.4, pp.34-41, 2001.
DOI : 10.1109/38.946629

A. A. Efros and T. K. Leung, Texture synthesis by non-parametric sampling, Proceedings of the Seventh IEEE International Conference on Computer Vision, p.1033, 1999.
DOI : 10.1109/ICCV.1999.790383
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.2805

P. Bénard, F. Cole, M. Kass, I. Mordatch, J. Hegarty et al., Stylizing animation by example, ACM Transactions on Graphics, vol.32, issue.4, pp.1-119, 2013.
DOI : 10.1145/2461912.2461929

C. Barnes, E. Shechtman, D. Goldman, and A. Finkelstein, The generalized patchmatch correspondence algorithm, " in Computer Vision ECCV 2010, ser. Lecture Notes in Computer Science, pp.29-43, 2010.

. Shum, Real-time texture synthesis by patch-based sampling, ACM Trans. Graph, vol.20, issue.3, pp.127-150, 2001.

W. Freeman, E. Pasztor, and O. Carmichael, Learning low-level vision, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.25-47, 2000.
DOI : 10.1109/ICCV.1999.790414
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.116.8559

X. Wang and X. Tang, Face photo-sketch synthesis and recognition, pp.1955-1967222, 2008.

Y. Weiss, Belief propagation and revision in networks with loops, 1997.

M. Elad and P. Milanfar, Style-transfer via texturesynthesis
DOI : 10.1109/tip.2017.2678168
URL : http://arxiv.org/abs/1609.03057

D. Ulyanov, A. Vedaldi, and V. S. Lempitsky, Instance normalization: The missing ingredient for fast stylization

B. J. Joshi, K. Stewart, and D. Shapiro, Bringing impressionism to life with neural style transfer in Canaletto sketch style Our results Results by Ruder et

. Fig, Real sequence results, where we compare out method to the neural artistic style transfer for videos [22]. For each style image, the first row corresponds to our method and the second row is [22]. Result comparison may be subjective and therefore challenging. Nevertheless, for the sketch style, it can be noted that our method stylize consistently the two walls of the bridge, while in the result of [22], the left wall is brighter and the right wall is darker. As remarked by [23], stylization by neural networks may be unpredictable at times. come swim

M. Ruder, A. Dosovitskiy, and T. Brox, Artistic Style Transfer for Videos
DOI : 10.1109/TVCG.2011.51
URL : http://arxiv.org/pdf/1604.08610

J. Fi?er, O. Jamri?ka, M. Luká?, E. Shechtman, P. Asente et al., StyLit, ACM Transactions on Graphics, vol.35, issue.4, 2016.
DOI : 10.1145/2897824.2925948

O. Frigo, N. Sabater, V. Demoulin, and P. Hellier, Optimal Transportation for Example-Guided Color Transfer, ACCV, pp.655-670, 2014.
DOI : 10.1007/978-3-319-16811-1_43

P. Weinzaepfel, J. Revaud, Z. Harchaoui, and C. Schmid, DeepFlow: Large Displacement Optical Flow with Deep Matching, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.175
URL : https://hal.archives-ouvertes.fr/hal-00873592

N. Sundaram, T. Brox, and K. Keutzer, Dense Point Trajectories by GPU-Accelerated Large Displacement Optical Flow, European Conference on Computer Vision (ECCV), ser. Lecture Notes in Computer Science, p.10, 2010.
DOI : 10.1007/978-3-642-15549-9_32

D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black, A Naturalistic Open Source Movie for Optical Flow Evaluation, European Conf. on Computer Vision (ECCV), ser. Part IV, pp.611-625, 2012.
DOI : 10.1007/978-3-642-33783-3_44
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.399.5529