Image Inpainting: A Review
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DOI: 10.1007/s11063-019-10163-0
Abstract: Although image inpainting, or the art of repairing the old and deteriorated images, has been around for many years, it has recently gained even more popularity, because of the recent development in image processing techniques.… read more here.
Keywords: image; paper; image inpainting; image processing ... See more keywords
Image Inpainting Based on Patch-GANs
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DOI: 10.1109/access.2019.2909553
Abstract: In this paper, we propose a novel image inpainting framework that takes advantage of holistic and structure information of the broken input image. Different from the existing models that complete the broken pictures using the… read more here.
Keywords: image inpainting; based patch; inpainting based; image ... See more keywords
Image Inpainting Based on Generative Adversarial Networks
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DOI: 10.1109/access.2020.2970169
Abstract: 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… read more here.
Keywords: image inpainting; inpainting based; image; generator ... See more keywords
Low Dimensional Manifold Regularization Based Blind Image Inpainting and Non-Uniform Impulse Noise Recovery
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DOI: 10.1109/access.2020.3035532
Abstract: Blind image inpainting is a challenging task in image processing. Motivated by the excellent performance of low dimensional manifold model (LDMM) in image inpainting for large-scale pixels missing, we introduce a novel blind inpainting model… read more here.
Keywords: image inpainting; dimensional manifold; low dimensional; image ... See more keywords
Semantic-SCA: Semantic Structure Image Inpainting With the Spatial-Channel Attention
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DOI: 10.1109/access.2021.3051982
Abstract: Deep learning has brought unprecedented progress to image inpainting. However, the existing methods often generate images with blurry textures and distorted structures because they may either fail to maintain semantic consistency or restore fine-grained textures.… read more here.
Keywords: image inpainting; structure; spatial channel; semantic structure ... See more keywords
Lightweight Generative Network for Image Inpainting Using Feature Contrast Enhancement
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DOI: 10.1109/access.2022.3198974
Abstract: With the help of the convolutional neural network (CNN) and generative adversarial network (GAN), image inpainting has achieved remarkable advances in performance. However, there are still some bottleneck problems to be solved, such as unnatural… read more here.
Keywords: feature contrast; network; image inpainting; image ... See more keywords
Collaborative Contrastive Learning-Based Generative Model for Image Inpainting
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DOI: 10.1109/access.2022.3211961
Abstract: The critical challenge of image inpainting is to infer reasonable semantics and textures for a corrupted image. Typical methods for image inpainting are built upon some prior knowledge to synthesize the complete image. One potential… read more here.
Keywords: image inpainting; collaborative contrastive; c2lgm; contrastive learning ... See more keywords
RF-Inpainter: Multimodal Image Inpainting Based on Vision and Radio Signals
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DOI: 10.1109/access.2022.3214972
Abstract: This study demonstrates the feasibility of image inpainting using both visual information and radio frequency (RF) signals. Recent developments in imaging and vision-based technologies using RF signals have revealed the potential of leveraging multimodal information… read more here.
Keywords: image inpainting; radio; inpainter multimodal; image ... See more keywords
Image Inpainting Based on Structural Constraint and Multi-Scale Feature Fusion
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DOI: 10.1109/access.2023.3246062
Abstract: When repairing masked images based on deep learning, there is usually insufficient representation of multi-level information and inadequate utilization of long distance features. To solve the problems, this paper proposes a second-order generative image inpainting… read more here.
Keywords: multi scale; fusion; image inpainting; feature ... See more keywords
Rank-One Matrix Approximation With ℓp-Norm for Image Inpainting
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DOI: 10.1109/lsp.2020.2988596
Abstract: In the problem of image inpainting, one popular approach is based on low-rank matrix completion. Compared with other methods which need to convert the image into vectors or dividing the image into patches, matrix completion… read more here.
Keywords: image inpainting; tex math; matrix; inline formula ... See more keywords
SRInpaintor: When Super-Resolution Meets Transformer for Image Inpainting
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2022.3190142
Abstract: Recent image inpainting methods have achieved remarkable improvements by using generative adversarial networks (GAN). Most of them have been designed to produce plausible results from high-level semantic features using only high-resolution (HR) supervision. However, because… read more here.
Keywords: image inpainting; super resolution; resolution; inpainting srinpaintor ... See more keywords