Results 11 to 20 of about 946,624 (201)
Continuous Facial Motion Deblurring [PDF]
IEEE Access, 2022 We introduce a novel framework for continuous facial motion deblurring that restores the continuous sharp moment latent in a single motion-blurred face image via a moment control factor.
Tae Bok Lee, Sujy Han, Yong Seok Heo
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Motion Deblurring of Faces [PDF]
International Journal of Computer Vision, 2018 Face analysis is a core part of computer vision, in which remarkable progress has been observed in the past decades. Current methods achieve recognition and tracking with invariance to fundamental modes of variation such as illumination, 3D pose, expressions.
Grigorios G. Chrysos +2 more
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Perceptual quality evaluation for motion deblurring
IET Computer Vision, 2018 Motion deblurring has been widely studied. However, the relevant quality evaluation of motion deblurred images remains an open problem. The motion deblurred images are usually contaminated by noise, ringing and residual blur (NRRB) simultaneously ...
Bo Hu, Leida Li, Jiansheng Qian
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Robust dual motion deblurring [PDF]
2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008 This paper presents a robust algorithm to deblur two consecutively captured blurred photos from camera shaking. Previous dual motion deblurring algorithms succeeded in small and simple motion blur and are very sensitive to noise. We develop a robust feedback algorithm to perform iteratively kernel estimation and image deblurring.
Jia Chen 0026 +3 more
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Rolling shutter motion deblurring [PDF]
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015 Although motion blur and rolling shutter deformations are closely coupled artifacts in images taken with CMOS image sensors, the two phenomena have so far mostly been treated separately, with deblurring algorithms being unable to handle rolling shutter wobble, and rolling shutter algorithms being incapable of dealing with motion blur.
Shuochen Su, Wolfgang Heidrich
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Depth-aware motion deblurring [PDF]
2012 IEEE International Conference on Computational Photography (ICCP), 2012 Motion deblurring from images that are captured in a scene with depth variation needs to estimate spatially-varying point spread functions (PSFs). We tackle this problemwith a stereopsis configuration, using depth information to help blur removal. We observe that the simple scheme to partition the blurred images into regions and estimate their PSFs ...
Li Xu 0001, Jiaya Jia
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Stochastic Blind Motion Deblurring [PDF]
IEEE Transactions on Image Processing, 2015 Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can, therefore, only be obtained with the help of prior information in the form of (often nonconvex) regularization terms for both the intrinsic image and the kernel.
Lei Xiao 0014 +3 more
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Self-Supervised Linear Motion Deblurring [PDF]
IEEE Robotics and Automation Letters, 2020 Motion blurry images challenge many computer vision algorithms, e.g, feature detection, motion estimation, or object recognition. Deep convolutional neural networks are state-of-the-art for image deblurring. However, obtaining training data with corresponding sharp and blurry image pairs can be difficult.
Peidong Liu 0001 +4 more
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Plenoptic Image Motion Deblurring
IEEE Transactions on Image Processing, 2018 We propose a method to remove motion blur in a single light field captured with a moving plenoptic camera. Since motion is unknown, we resort to a blind deconvolution formulation, where one aims to identify both the blur point spread function and the latent sharp image.
Paramanand Chandramouli +3 more
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Motion Deblurring in the Wild [PDF]
, 2017 The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the object.
Mehdi Noroozi +2 more
openaire +3 more sources