Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 5
1569-1577

Instance image coloring combined with fine-grained self attention

Liu Hang1
Pu Yuanyuan1,2
Wang Chengchao1
Zhao Zhengpeng1
Zhu Pengjie1
Xu Dan1
1. School of Information Science & Engineering, Yunnan University, Kunming 650504, China
2. The Universities Key Laboratory of Internet of Things Technology & Application, Kunming 650504, China
DOI: 10.19734/j.issn.1001-3695.2023.08.0393

Abstract

Although deep learning-based image coloring methods have achieved significant results, but there are still suffer from three problems: redundant stain, color dimming, and color deviation. To this end, this paper proposed an instance image coloring method combined with fine-grained attention(fine-grain self-attention, FGSA). Specifically, it firstly divided the extracted feature maps into color and spatial location, and combined the two parts of the fittingto improve the correspondence between the color and the spatial location of the image to mitigate the redundant color patches. Secondly, inspired by the principle of HDR for optical photography, it utilized convolutional kernels with small sensory fields to enhance or suppress the color features of the image, and combined them with softmax to dynamically map the features, thus improving contrast and alleviating the darkness of the coloring. Finally, combining different nonlinear basis functions increased the network's representation of nonlinear colors and fitted a color distribution that was closest to the real image to address color bias. Extensive experimental results show that the proposed method achieves satisfactory results in instance image coloring. In particular, compared with the state-of-the-art methods, the proposed method improves 4.1% and 7.9% in feature perception evaluation indexes LPIPS and FID, respectively.

Foundation Support

国家自然科学基金资助项目(61761046)
云南省科技厅应用基础研究计划重点项目(202001BB050043)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.08.0393
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 5
Section: Technology of Graphic & Image
Pages: 1569-1577
Serial Number: 1001-3695(2024)05-041-1569-09

Publish History

[2023-11-01] Accepted Paper
[2024-05-05] Printed Article

Cite This Article

刘航, 普园媛, 王成超, 等. 结合细粒度自注意力的实例图像着色 [J]. 计算机应用研究, 2024, 41 (5): 1569-1577. (Liu Hang, Pu Yuanyuan, Wang Chengchao, et al. Instance image coloring combined with fine-grained self attention [J]. Application Research of Computers, 2024, 41 (5): 1569-1577. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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