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Fine-Grained Video Deblurring with Event Camera
2021Despite CNN-based deblurring models have shown their superiority on solving motion blurs, how to restore photorealistic images from severe motion blurs remains an ill-posed problem due to the loss of temporal information and textures. Video deblurring methods try to extract meaningful temporal information in multiple consecutive blurry frames during a ...
Limeng Zhang +5 more
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Image/video deblurring using a hybrid camera
2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008We propose a novel approach to reduce spatially varying motion blur using a hybrid camera system that simultaneously captures high-resolution video at a low-frame rate together with low-resolution video at a high-frame rate. Our work is inspired by Ben-Ezra and Nayar who introduced the hybrid camera idea for correcting global motion blur for a single ...
null Yu-Wing Tai +3 more
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Bundled Kernels for Nonuniform Blind Video Deblurring
IEEE Transactions on Circuits and Systems for Video Technology, 2017We present a novel blind video deblurring approach by estimating a bundle of kernels and applying the residual deconvolution. Our approach adopts multiple kernels to represent spatially varying motion blur, and thus can cope with nonuniform video deblurring.
Lei Zhang, Le Zhou, Hua Huang
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Face Video Deblurring Using 3D Facial Priors
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019Existing face deblurring methods only consider single frames and do not account for facial structure and identity information. These methods struggle to deblur face videos that exhibit significant pose variations and misalignment. In this paper we propose a novel face video deblurring network capitalizing on 3D facial priors.
Wenqi Ren +5 more
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Deblurring via Video Diffusion Models
Poster Volume Ⅰ The 2024 Twentieth International Conference on Intelligent Computing August 5-8, 2024 Tianjin, ChinaVideo deblurring poses a significant challenge due to the intricate nature of blur, which often arises from a confluence of factors such as camera shakes, object motions, and variations in depth. While diffusion models and video diffusion models have respectively shone brightly in the fields of image and video generation, achieving remarkable results ...
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Bidirectional Transformer for Video Deblurring
IEEE Transactions on Circuits and Systems for Video Technology, 2022Qian Xu, Yuntao Qian
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2022 5th International Conference on Computing and Big Data (ICCBD), 2022
Haoyu Wang, Jiawei Niu
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Haoyu Wang, Jiawei Niu
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Learning Event-Driven Video Deblurring and Interpolation
2020Event-based sensors, which have a response if the change of pixel intensity exceeds a triggering threshold, can capture high-speed motion with microsecond accuracy. Assisted by an event camera, we can generate high frame-rate sharp videos from low frame-rate blurry ones captured by an intensity camera.
Songnan Lin +7 more
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Deep Video Deblurring for Hand-Held Cameras
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on the alignment of nearby frames.
Shuochen Su +5 more
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Three-Stage Motion Deblurring from a Video
2007In this paper, a novel approach is proposed to remove the motion blur from a video, which is degraded and distorted by fast camera motion. Our approach is based on the image statistics rather than the traditional motion estimation. The image statistics has been successfully applied for blind motion deblurring for a single image by Fergus et al [3] and ...
Chunjian Ren, Wenbin Chen, I-fan Shen
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