Image Inpainting Based on Generative Adversarial Networks

Image Inpainting Based on Generative Adversarial Networks

Image inpainting aims to fill missing regions of a damaged image with plausibly synthesized content. Existing methods for image inpainting either fill the missing regions by borrowing information from surrounding areas or generating semantically coherent content from region context. They often produ...

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Bibliographic Details
Main Authors: Yi Jiang, Jiajie Xu, Baoqing Yang, Jing Xu, Junwu Zhu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
AutoEncoder
image inpainting
skip-connection
stable training
wasserstein GAN
Online Access:https://ieeexplore.ieee.org/document/8974211/

Internet

https://ieeexplore.ieee.org/document/8974211/

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