- Home
- Archives
- 2024
- Vol. 5 Issue 3
- Article
Grayscale Image Colorization
Authors
123Students, Department of Computer Science and Engineering, School of Management Sciences Lucknow, Uttar Pradesh, India. 4Assistant Professor, Department of Computer Science and Engineering, School of Management Sciences Lucknow, Uttar Pradesh, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 5, Issue 3 (2024)
- Published Online
- May-June 2024
- Pages
- 100-104
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
[1] T. Welsh, M. Ashikhmin, and K. Mueller, “Transferring color to grayscale image,” ACM Transactional on Graphics, vol. 21, no. 3,
pp. 277-280, 2002.
[2] R. Irony, D. Cohen-Or, and D. Lischinski, “Colorization by example,” in EurographicsSymp. on Rendering, vol. 2. Citeseer, 2005.
[3] X. Liu, L. Wan, Y. Qu, T.-T. Wong, S. Lin, C.-S. Leung, and P.-A. Heng, “Intrinsic colorization,” in TOG, vol. 27, no. 5. ACM, 2008,
p. 152.
[4] Y.-S. Chia, S. Zhuo, R. K. Gupta, Y.-W. Tai, S.-Y. Cho, P. Tan, and S. Lin, “Semantic colorization with internet images,” in TOG,
vol. 30, no. 6. ACM, 2011, p. 156.
[5] Z. Cheng, Q. Yang, and B. Sheng, “Deep colorization,” In Proceedings of the IEEE International Conference on Computer Vision
(ICCV), pp. 415– 423, 2015.
[6] G. Larsson, M. Maire, and G. Shakhnarovich, “Learning representations for automatic colorization,” In Proceedings of the
European Conference on Computer Vision (ECCV), pp. 577–593, 2016.
[7] R. Zhang, P. Isola, and A.A. Efros, “Colorful image colorization,” In Proceedings of European Conference on Computer Vision
(ECCV), pp. 649–666, 2016
[8] 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, vol. 35, no. 4, pp. 110:1-110:11,
2016.
[9] R. Zhang, J. Zhu, P. Isola, X. Geng, A.S. Lin, T. Yu, and A.A. Efros, “Real-time user-guided image colorization with learned deep
priors,” ACM Transactions n Graphics, vol. 36, no. 4, pp. 119:1-119:11, 2017.
[10] K. He, X. Zhang, S. Ren, and J. Sun, “Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,”
in Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 1026–1034.
[11] Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in
neural information processing systems, 2012, pp. 1097–1105.
[12] W. Ouyang and X. Wang, “Joint deep learning for pedestrian detection,” in ICCV. IEEE, 2013, pp. 2056–2063.
[13] C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution,” in ECCV. Springer,
2014, pp. 184–199.
[14] Z. Yan, H. Zhang, B. Wang, S. Paris, and Y. Yu, “Automatic photo adjustment using deep neural networks,” ACM Trans. Graph.,
vol. 35, no. 2, pp. 11:1–11:15, Feb. 2016.
pp. 277-280, 2002.
[2] R. Irony, D. Cohen-Or, and D. Lischinski, “Colorization by example,” in EurographicsSymp. on Rendering, vol. 2. Citeseer, 2005.
[3] X. Liu, L. Wan, Y. Qu, T.-T. Wong, S. Lin, C.-S. Leung, and P.-A. Heng, “Intrinsic colorization,” in TOG, vol. 27, no. 5. ACM, 2008,
p. 152.
[4] Y.-S. Chia, S. Zhuo, R. K. Gupta, Y.-W. Tai, S.-Y. Cho, P. Tan, and S. Lin, “Semantic colorization with internet images,” in TOG,
vol. 30, no. 6. ACM, 2011, p. 156.
[5] Z. Cheng, Q. Yang, and B. Sheng, “Deep colorization,” In Proceedings of the IEEE International Conference on Computer Vision
(ICCV), pp. 415– 423, 2015.
[6] G. Larsson, M. Maire, and G. Shakhnarovich, “Learning representations for automatic colorization,” In Proceedings of the
European Conference on Computer Vision (ECCV), pp. 577–593, 2016.
[7] R. Zhang, P. Isola, and A.A. Efros, “Colorful image colorization,” In Proceedings of European Conference on Computer Vision
(ECCV), pp. 649–666, 2016
[8] 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, vol. 35, no. 4, pp. 110:1-110:11,
2016.
[9] R. Zhang, J. Zhu, P. Isola, X. Geng, A.S. Lin, T. Yu, and A.A. Efros, “Real-time user-guided image colorization with learned deep
priors,” ACM Transactions n Graphics, vol. 36, no. 4, pp. 119:1-119:11, 2017.
[10] K. He, X. Zhang, S. Ren, and J. Sun, “Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,”
in Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 1026–1034.
[11] Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in
neural information processing systems, 2012, pp. 1097–1105.
[12] W. Ouyang and X. Wang, “Joint deep learning for pedestrian detection,” in ICCV. IEEE, 2013, pp. 2056–2063.
[13] C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution,” in ECCV. Springer,
2014, pp. 184–199.
[14] Z. Yan, H. Zhang, B. Wang, S. Paris, and Y. Yu, “Automatic photo adjustment using deep neural networks,” ACM Trans. Graph.,
vol. 35, no. 2, pp. 11:1–11:15, Feb. 2016.
Related Articles
Share Article
*Instagram doesn't support direct link sharing from web. Copy the link and share it in your Instagram story or post.