TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Face inpainting via Learnable Structure Knowledge of Fusion Network |
| 영문제목(English Title) |
Face inpainting via Learnable Structure Knowledge of Fusion Network |
| 저자(Author) |
Beomjoong Kim
Hyoung Joong Kim
Junghee Le
You Yang
Sixun Liu
Bin Xing3
Kesen Li
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| 원문수록처(Citation) |
VOL 16 NO. 03 PP. 0877 ~ 0893 (2022. 03) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%. |
| 키워드(Keyword) |
Blockchain
central bank digital currency (CBDC)
cryptoasset
distributed ledger technology (DLT)
smart contract
Face Inpainting
Image Edge
Gated Convolution
Region Normalization
Prior Knowledge
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| 파일첨부 |
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