A Video Deblurring Algorithm Based on Motion Vector and An Encorder-Decoder Network
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DOI: 10.1109/access.2019.2923759
Abstract: Camera shakes cause video motion blur. Video deblurring has been studied for years, and however, there are still unresolved problems, such as video frame alignment, frame selection, and frame ambiguity evaluation. We propose a video… read more here.
Keywords: video; motion vector; algorithm based; video deblurring ... See more keywords
Recursive Neural Network for Video Deblurring
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DOI: 10.1109/tcsvt.2020.3035722
Abstract: Video deblurring is still a challenging low-level vision task since spatio-temporal characteristics across both the spatial and temporal domains are difficult to model. In this article, to model the temporal information, we develop a non-local… read more here.
Keywords: network video; video; recursive neural; neural network ... See more keywords
Learning an Occlusion-Aware Network for Video Deblurring
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3132102
Abstract: Video deblurring is a challenging task since the blur is caused by camera shake, object motions, etc. The success of the state-of-the-art methods stems mainly from exploiting the temporal information of neighboring frames through alignment.… read more here.
Keywords: aware network; video; video deblurring; occlusion aware ... See more keywords
VDTR: Video Deblurring With Transformer
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3201045
Abstract: Video deblurring is still an unsolved problem due to the challenging spatio-temporal modeling process. While existing convolutional neural network (CNN)-based methods show a limited capacity of effective spatial and temporal modeling for video deblurring. This… read more here.
Keywords: vdtr; temporal modeling; transformer based; video ... See more keywords
Deep Video Deblurring Using Sharpness Features From Exemplars
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DOI: 10.1109/tip.2020.3023534
Abstract: Video deblurring is a challenging problem as the blur in videos is usually caused by camera shake, object motion, depth variation, etc. Existing methods usually impose handcrafted image priors or use end-to-end trainable networks to… read more here.
Keywords: using sharpness; sharpness features; video deblurring; image ... See more keywords
Geometry-Aware Deep Video Deblurring via Recurrent Feature Refinement
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2021.3137019
Abstract: Blurring in videos is a frequent phenomenon in real-world video data owing to camera shake or object movement at different scene depths. Hence, video deblurring is an ill-posed problem that requires understanding of geometric and… read more here.
Keywords: information; deep video; geometry; model ... See more keywords
Real‐Time Video Deblurring via Lightweight Motion Compensation
Sign Up to like & getrecommendations! Published in 2022 at "Computer Graphics Forum"
DOI: 10.1111/cgf.14667
Abstract: While motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead. This paper proposes a real‐time video deblurring framework consisting of a lightweight multi‐task unit that supports… read more here.
Keywords: motion compensation; video deblurring; real time;