An analysis: different methods about line art colorization

Jinhui Gao; Ruihao Zeng; Yuan Liang; Xinyu Diao

doi:10.1117/12.2641852

10 November 2022 An analysis: different methods about line art colorization

Jinhui Gao, Ruihao Zeng, Yuan Liang, Xinyu Diao

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 123483X (2022) https://doi.org/10.1117/12.2641852
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

We have conducted a series of studies and analyses to address the problem of line art colorization. We chose Generative Adversarial Networks (GANs), a leading neural network architecture for solving this problem, as our focus. For a large number of studies based on this architecture, we improved, applied, and analytically compared four methods, pix2pix, pix2pixHD, white-box, and scaled Fourier transform (SCFT), which can represent the mainstream problem-solving direction in the field of line colorization to the greatest extent possible. Finally, two reference quantities were introduced to quantify the results of the analysis.

Citation Download Citation

Jinhui Gao, Ruihao Zeng, Yuan Liang, and Xinyu Diao "An analysis: different methods about line art colorization", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 123483X (10 November 2022); https://doi.org/10.1117/12.2641852

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