Enhancing Video Colorization with Deep Learning: A Comprehensive Analysis of Training Loss Functions

Author:

Stival Leandro,da Silva Torres Ricardo,Pedrini Helio

Publisher

Springer Nature Switzerland

Reference39 articles.

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2. Akimoto, N., Hayakawa, A., Shin, A., Narihira, T.: Reference-based video colorization with spatiotemporal correspondence. CoRR, abs/2011.12528:1–14 (2020)

3. Anwar, S., Tahir, M., Li, C., Mian, A., Khan, F.S., Muzaffar, A.W.. Image colorization: a survey and dataset. arXiv preprint arXiv:2008.10774 (2020)

4. Ding, K., Ma, K., Wang, S., Simoncelli, E.P.: Comparison of full-reference image quality models for optimization of image processing systems. Int. J. Comput. Vis. 129(4), 1258–1281 (2021)

5. Pelin Doğan, Tunç Ozan Aydın, Nikolce Stefanoski, and Aljoscha Smolic. Key-Frame Based Spatiotemporal Scribble Propagation. In: Eurographics Workshop on Intelligent Cinematography and Editing, pp. 13–20 (2015)

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