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Structure-guided Generative Adversarial Network for Image Inpainting Cover

Structure-guided Generative Adversarial Network for Image Inpainting

International Journal of Advanced Network, Monitoring and Controls
Volume 9 (2024): Issue 4 (December 2024)
By: Huan Liang,  Li Zhao and  Lei Cao  
Open Access
|Dec 2024
Figures & tables

Figures & Tables

Figure 1.

Overall structure of the image inpainting network

Figure 2.

Schematic diagram of gated convolution structure

Figure 3.

Curves of Loss Functions during Model Training

Figure 4.

A partial sample of the Places2 dataset

Figure 5.

A partial sample of the CelebA dataset

Figure 6.

A partial sample of the Irregular mask dataset

Figure 7.

The repair effect of each algorithm is displayed

Figure 8.

Comparison of Inpainting Results at Different Iterations during Training

PSNR/SSIM for different image inpainting methods and different mask area ratios on the places2 dataset

Mask RatioPSNR/SSIM
CEPconvECOurs
1%-10%29.26/0.93730.87/0.92932.58/0.94733.89/0.961
10%-20%21.34/0.74624.62/0.88727.15/0.91628.43/0.935
20%-30%19.58/0.65821.43/0.82424.33/0.85925.58/0.878
30%-40%17.82/0.54919.32/0.75123.17/0.78223.81/0.814
40%-50%15.77/0.47517.48/0.68221.64/0.74722.04/0.763
50%-60%14.25/0.41616.44/0.61319.46/0.65120.53/0.686
DOI: https://doi.org/10.2478/ijanmc-2024-0031 | Journal eISSN: 2470-8038
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Language: English
Page range: 1 - 8
Published on: Dec 31, 2024
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Image Inpainting,
Edge Detection,
Generative Adversarial Network,
Gated Convolution,
Deep Learning
Related subjects:
Computer sciences,
Computer sciences, other

© 2024 Huan Liang, Li Zhao, Lei Cao, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 9 (2024): Issue 4 (December 2024)
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