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Blind Image Inpainting with Sparse Directional Filter Dictionaries for Lightweight CNNs
Blind inpainting algorithms based on deep learning architectures have shown a remarkable performance in recent years, typically outperforming...
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Blind image inpainting quality assessment using local features continuity
This paper deals with Blind Inpainted Image Quality Assessment BIIQA. Herein, we propose a new method that exploits the continuity of features around...
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Deep Learning-Based Image and Video Inpainting: A Survey
Image and video inpainting is a classic problem in computer vision and computer graphics, aiming to fill in the plausible and realistic content in...
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HSVConnect: HSV guided enhanced content generation network for image inpainting
With the introduction of structural information, image inpainting technology has made great progress in inpainting large missing areas. However, most...
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SFI-Swin: symmetric face inpainting with swin transformer by distinctly learning face components distributions
Image inpainting consists of filling holes or missing parts of an image. Inpainting face images with symmetric characteristics is more challenging...
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CTNet: hybrid architecture based on CNN and transformer for image inpainting detection
Digital image inpainting technology has increasingly gained popularity as a result of the development of image processing and machine vision....
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DKH: a hybridized approach for image inpainting using Bayes probabilistic-based image fusion
Image inpainting is the process of removing the unwanted objects from the image or it refers to the restoration of the original image. Despite the...
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Mask removal : Face inpainting via attributes
Due to the outbreak of the COVID-19 pandemic, wearing masks in public areas has become an effective way to slow the spread of disease. However, it...
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Image Inpainting Forensics Algorithm Based on Dual-Domain Encoder-Decoder Network
Image inpainting can fill regions of images with plausible content and can also be used to remove specific objects and leave only faint traces in...
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The Family of Onion Convolutions for Image Inpainting
Recently deep learning methods have achieved great success in image inpainting problem. However, reconstructing continuities of complex structures...
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Multiplicative noise removal and blind inpainting of ultrasound images based on a new variational framework
Image inpainting and denoising are two important preprocessing steps widely used in image and visual analysis. In this paper, by the maximum a...
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A survey on digital image forensic methods based on blind forgery detection
In the current digital era, images have become one of the key channels for communication and information. There are multiple platforms where digital...
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A novel CNN framework for skin disease classification using adaptive percentage filter for image binarization and fast-marching inpainting method
Artificial intelligence assists medical practitioners with disease diagnosis from acute to chronic illnesses and has brought significant breakthrough...
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VCNet: A Robust Approach to Blind Image Inpainting
Blind inpainting is a task to automatically complete visual contents without specifying masks for missing areas in an image. Previous work assumes...
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Blind bleed-through removal in color ancient manuscripts
Archaic manuscripts are an important part of ancient civilization. Unfortunately, such documents are often affected by various age related...
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Masking Based De Trop Noise Exclusion and Image Inpainting Instance Restoration
Skin cancer has shown a rapidly growing event rate, highlighting skin cancer as a significant issue for general well-being. Impediment due to...
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Image Inpainting: A Review
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...
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Blind MRI Brain Lesion Inpainting Using Deep Learning
In brain image analysis many of the current pipelines are not robust to the presence of lesions which degrades their accuracy and robustness. For...
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Exploring Image Transformations with Diffusion Models: A Survey of Applications and Implementation Code
Diffusion Models have become increasingly popular in recent years and their applications span a wide range of fields. This survey focuses on the use...
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Deep learning adversarial attacks and defenses on license plate recognition system
The breakthroughs in Machine learning and deep neural networks have revolutionized the handling of critical practical challenges, achieving...
