Results 31 to 40 of about 1,364,847 (158)
Human and Scene Motion Deblurring Using Pseudo-Blur Synthesizer
IEEE Access, 2021 Present-day deep learning-based motion deblurring methods utilize the pair of synthetic blur and sharp data to regress any particular framework. This task is designed for directly translating a blurry image input into its restored version as output.
Jonathan Samuel Lumentut, In Kyu Park
doaj +1 more source
SL-CycleGAN: Blind Motion Deblurring in Cycles using Sparse Learning [PDF]
, 2022 In this paper, we introduce an end-to-end generative adversarial network (GAN) based on sparse learning for single image motion deblurring, which we called SL-CycleGAN.
Liu, Zhiyong +5 more
core +1 more source
Efficient Video Deblurring Guided by Motion Magnitude
, 2022 Video deblurring is a highly under-constrained problem due to the spatially and temporally varying blur. An intuitive approach for video deblurring includes two steps: a) detecting the blurry region in the current frame; b) utilizing the information from
Wang, Yusheng +6 more
core +2 more sources
Robust Single Image Deblurring Using Gyroscope Sensor
IEEE Access, 2021 Motion blur in an image is caused by the movement of the camera during exposure time; thus, awareness of the camera motion is a key factor in image deblurring algorithms.
Seowon Ji +4 more
doaj +1 more source
Depth-aware motion deblurring [PDF]
, 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.
Xu, Li, Jia, Jiaya, Jiaya Jia, Li Xu
core +1 more source
Real-Time Video Deblurring via Lightweight Motion Compensation
, 2022 While motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead.
Son, Hyeongseok +7 more
core +1 more source
SID: Sensor-Assisted Image Deblurring System for Mobile Devices
IEEE Access, 2019 Handheld mobile photography is often affected by motion blur due to the difficulty of keeping the camera's stable. The existing processing method is usually a high-cost deblurring process of a computer, which seriously affects the user experience, and ...
Qing Wang +4 more
doaj +1 more source
Differentiable Neural Architecture Search Method for Blind Image Deblurring [PDF]
Jisuanji gongcheng, 2021 The design of neural networks for image deblurring requires heavy work of manual parameter tuning. To address the problem, a differentiable neural network search method for image deblurring is proposed.
MIAO Si, ZHU Yongxin
doaj +1 more source
Self-Supervised Linear Motion Deblurring
, 2020 Motion blurry images challenge many computer vision algorithms, e.g., feature detection, motion estimation, or object recognition. Deep convolutional neural networks are stateof-the-art for image deblurring.
Janai, Joel, +14 more
core +1 more source
Motion Blur Removal for Uav-Based Wind Turbine Blade Images Using Synthetic Datasets
Remote Sensing, 2021 Unmanned air vehicle (UAV) based imaging has been an attractive technology to be used for wind turbine blades (WTBs) monitoring. In such applications, image motion blur is a challenging problem which means that motion deblurring is of great significance ...
Yeping Peng +4 more
doaj +1 more source