CLIP-RL: Closed-Loop Video Inpainting with Detection-Guided Reinforcement Learning [PDF]
SensorsExisting video inpainting methods typically combine optical flow propagation with Transformer architectures, achieving promising inpainting results.
Meng Wang +3 more
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Feedback Recorrection Semantic-Based Image Inpainting Under Semi-Supervised Learning [PDF]
SensorsImage semantics, by revealing rich structural information, provides crucial guidance for image inpainting. However, current semantic-guided inpainting frameworks generally operate unidirectionally, relying on pre-trained segmentation networks without a ...
Xueyi Ye +4 more
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Survey of Research on Image Inpainting Methods [PDF]
Jisuanji kexue yu tansuo, 2022 Image inpainting refers to restoring the pixels in damaged areas of an image to make them as consistent as possible with the original image. Image inpainting is not only crucial in the computer vision tasks, but also serves as an important cornerstone of
LUO Haiyin, ZHENG Yuhui
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Multi-Step Structure Image Inpainting Model with Attention Mechanism
Sensors, 2023 The proliferation of deep learning has propelled image inpainting to an important research field. Although the current image inpainting model has made remarkable achievements, the two-stage image inpainting method is easy to produce structural errors in ...
Cai Ran, Xinfu Li, Fang Yang
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Face Inpainting Algorithm Combining Edge Information with Gated Convolution
Jisuanji kexue yu tansuo, 2021 For the face inpainting under arbitrary shape occlusion, the existing methods are easy to produce edge blur and distortion of the inpainting results. In this paper, an algorithm for face inpainting combining edge information with gated convolution is ...
WANG Fuping, LI Wenlou, LIU Ying, LU Jin, GONG Yanchao
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RF-Inpainter: Multimodal Image Inpainting Based on Vision and Radio Signals
IEEE Access, 2022 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
Cheng Chen +3 more
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An adaptive image inpainting method based on the modified mumford-shah model and multiscale parameter estimation [PDF]
Компьютерная оптика, 2019 Image inpainting is a process of filling missing and damaged parts of image. By using the Mumford-Shah image model, the image inpainting can be formulated as a constrained optimization problem.
Dang Ngoc Hoang Thanh +3 more
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A Review of Image Inpainting Methods Based on Deep Learning
Applied Sciences, 2023 Image Inpainting is an age-old image processing problem, with people from different eras attempting to solve it using various methods. Traditional image inpainting algorithms have the ability to repair minor damage such as scratches and wear.
Zishan Xu +6 more
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Image Inpainting Based on Interactive Separation Network and Progressive Reconstruction Algorithm
IEEE Access, 2022 Recently, learning-based image inpainting has gained much attention. It widely utilizes an auto-encoder structure and can obtain compact feature representation in the encoder to achieve high-quality image inpainting.
Jun Gong +6 more
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Fragments Inpainting for Tomb Murals Using a Dual-Attention Mechanism GAN with Improved Generators
Applied Sciences, 2023 As the only underground mural in the collection, the tomb murals are subject to damage due to temperature, humidity, and foundation settlement changes. Traditional mural inpainting takes a long time and requires experts to draw it manually.
Meng Wu, Xiao Chang, Jia Wang
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