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Deblur Capsule Networks
Blur is often caused by physical limitations of the image acquisition sensor or by unsuitable environmental conditions. Blind image deblurring...
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RT-Deblur: real-time image deblurring for object detection
After a long period of research and development, 2D image object detection technology has been greatly improved in terms of efficiency and accuracy,...
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Two-stage single image Deblurring network based on deblur kernel estimation
Image deblurring for dynamic scenes is a serious challenge in computer vision. Motion blur is caused by camera shaking or object movement during the...
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Deblur and deep depth from single defocus image
In this paper, we tackle depth estimation and blur removal from a single out-of-focus image. Previously, depth is estimated, and blurred is removed...
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Real-World Image Deblurring via Unsupervised Domain Adaptation
Most deep learning models for image deblurring are trained on pairs of clean images and their blurry counterparts, where the blurry inputs are...
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DC-Deblur: A Dilated Convolutional Network for Single Image Deblurring
Single image deblurring is a significant and challenging task in image processing vision and machine learning. Convolutional Neural Network (CNN)...
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Event-Based Image Deblurring with Dynamic Motion Awareness
Non-uniform image deblurring is a challenging task due to the lack of temporal and textural information in the blurry image itself. Complementary...
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A multiscale network for deblurring coal slurry foam images
Deblurring coal slurry foam images is critical for coal slurry flotation condition identification. To improve the quality of images acquired in...
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Dynamic selection of proper kernels for image deblurring: a multistrategy design
The non-blind deblurring approach can adequately deblur single-blur images by applying a suitable mathematical model. In contrast, it cannot...
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WTransU-Net: Wiener deconvolution meets multi-scale transformer-based U-net for image deblurring
Deblurring is a classical image restoration problem. Although recent methods have shown promising deblurring performance, most methods still cannot...
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Deformable multi-scale fusion network for non-uniform single image deblurring
Non-uniform image deblurring is an ill-posed problem. Previous research efforts attempt to solve this problem by increasing the number of scales...
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Deblurring Low-Light Images with Events
Modern image-based deblurring methods usually show degenerate performance in low-light conditions since the images often contain most of the poorly...
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Estimating Blur Parameters to Reconstruct the Motion Blurred Images
One of the important topics of image restoration is the restoration of a motion-blurred image. The restored blurred images are based on estimating...
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Image region driven prior selection for image deblurring
Deblurring an image has been a long researched problem. This problem is very complex due to the lack of sufficient information about the blur...
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Fading regularization MFS algorithm for the Cauchy problem associated with the two-dimensional Stokes equations
In this paper, we investigate the application of the fading regularization method with the method of fundamental solutions (MFS) to the ill-posed...
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Multi-DIP: A General Framework for Unsupervised Multi-degraded Image Restoration
Most existing image restoration algorithms only perform a single task. But in the real world, the degradation pattern could be much more complex,...
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Spatio-Temporal Learning for Video Deblurring based on Two-Stream Generative Adversarial Network
Video-deblurring has achieved excellent results by using deep learning approaches. How to capture the dynamic spatio-temporal information in the...
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A Deep Convolutional Encoder–Decoder–Restorer Architecture for Image Deblurring
The accuracy of many computer vision tasks is reduced by blurred images, so deblur is important. More details of the image can be captured by a...
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Multi-scale recursive codec network with authority parameters (MRCN-AP) for RFID multi-label deblurring
The dynamic non-uniform blur caused by Radio Frequency Identification (RFID) multi-label motion seriously affects the identification and location of...
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Blind deblurring of QR code using intensity and gradient prior of positioning patterns
QR codes are widely used in the traceability of commodities, but the QR codes are easy to become blurred during the acquisition process of mobile...
