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We review some of the most recent approaches to colorize gray-scale images using deep learning methods.
The cie 1976 color-difference formulae
Robertson, A.R.: · 1977
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Transferring color to greyscale images
Welsh, T., Ashikhmin, M., Mueller, K.: · 2002
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Feature Extraction & Image Processing for Computer Vision
Nixon, M.S., Aguado, A.S.: · 2002
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Cielab colorspace
Hoffman, G.: · 2003
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Colorization using optimization
Levin, A., Lischinski, D., Weiss, Y.: · 2004
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Colorization by example
Ironi, R., Cohen-Or, D., Lischinski, D.: · 2005
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Manga colorization
Qu, Y., Wong, T.T., Heng, P.A.: · 2006
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Automatic image colorization via multimodal predictions
Charpiat, G., Hofmann, M., Schölkopf, B.: · 2008
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A fast local descriptor for dense matching
Tola, E., Lepetit, V., Fua, P.: · 2008
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Scalable parallel programming with cuda
Nickolls, J., Buck, I., Garland, M., Skadron, K.: · 2008
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Lazybrush: Flexible painting tool for hand-drawn cartoons
Sỳkora, D., Dingliana, J., Collins, S.: · 2009
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2014
Cited alongside, same era.
Visualizing and understanding convolutional networks
Zeiler, M.D., Fergus, R.: · 2014
Cited alongside, same era.
Striving for simplicity: The all convolutional net
Springenberg, J.T., Dosovitskiy, A., Brox, T., Riedmiller, M.A.: · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2015
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Unsupervised diverse colorization via generative adversarial networks
Bora, D.J., Kumar Gupta, A., Ahmad Fayaz, K.: · 2015
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TensorFlow: Large-scale machine learning on heterogeneous systems (2015) Software available from tensorflow.org
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X.: · 2015
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Inception-v4, inception-resnet and the impact of residual connections on learning
Szegedy, C., Ioffe, S., Vanhoucke, V.: · 2016
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Kingma, D.P., Ba, J.: · 2014
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: · 2015
Cited alongside, same era.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., Sun, J.: · 2015
Cited alongside, same era.
Learning large-scale automatic image colorization
Deshpande, A., Rock, J., Forsyth, D.: · 2015
Cited alongside, same era.
Deep colorization
Cheng, Z., Yang, Q., Sheng, B.: · 2015
Cited alongside, same era.
He, K., Zhang, X., Ren, S., Sun, J.: · 2016
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Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
Iizuka, S., Simo-Serra, E., Ishikawa, H.: · 2016
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Colorful image colorization
Zhang, R., Isola, P., Efros, A.A.: · 2016
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Learning representations for automatic colorization
Larsson, G., Maire, M., Shakhnarovich, G.: · 2016
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Deep Learning
Goodfellow, I., Bengio, Y., Courville, A.: · 2016
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Real-time user-guided image colorization with learned deep priors
Zhang, R., Zhu, J.Y., Isola, P., Geng, X., Lin, A.S., Yu, T., Efros, A.A.: · 2017
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