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2018

Painting Outside the Box: Image Outpainting with GANs

Sabini, Mark, Rusak, Gili

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The challenging task of image outpainting (extrapolation) has received comparatively little attention in relation to its cousin, image inpainting (completion).

Accordingly, we present a deep learning approach based on Iizuka et al.
for adversarially training a network to hallucinate past image boundaries.
We use a three-phase training schedule to stably train a DCGAN architecture on a subset of the Places365 dataset.

Painting Outside the Box: Image Outpainting with GANs · Around

Built on

Biggerpicture: data-driven image extrapolation using graph matching
M. Wang, Y. Lai, Y. Liang, R. R. Martin, and S.-M. Hu · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng · 2015
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A neural algorithm of artistic style
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L. A. Gatys, A. S. Ecker, and M. Bethge · 2015
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