Improved Deep Multi-Patch Hierarchical Network With Nested Module for Dynamic Scene Deblurring
IEEE Access, 2020 Dynamic scene deblurring is a significant technique in the field of computer vision. The multi-scale strategy has been successfully extended to the deep end-to-end learning-based deblurring task.
Zunjin Zhao +3 more
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Image deblurring by multi-scale modified U-Net using dilated convolution
Science ProgressIn modern urban traffic systems, intersection monitoring systems are used to monitor traffic flows and track vehicles by recognizing license plates. However, intersection monitors often produce motion-blurred images because of the rapid movement of cars.
Xiao-Pei Shi +4 more
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Blind UAV Images Deblurring Based on Discriminative Networks
Sensors, 2018 Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image ...
Ruihua Wang +4 more
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Improved Motion Invariant Deblurring through Motion Estimation [PDF]
, 2014 We address the capture of sharp images of fast-moving objects, and build on the Motion Invariant photographic technique. The key advantage of motion invariance is that, unlike other computational photographic techniques, it does not require pre-exposure velocity estimation in order to ensure numerically stable deblurring.
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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 clear regions in adjacent frames for current frame deblurring. To realize this process, our idea is
Wang, Yusheng +6 more
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Motion-Adaptive Separable Collaborative Filters for Blind Motion Deblurring
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Eliminating image blur produced by various kinds of motion has been a challenging problem. Dominant approaches rely heavily on model capacity to remove blurring by reconstructing residual from blurry observation in feature space. These practices not only prevent the capture of spatially variable motion in the real world but also ignore the tailored ...
Liu, Chengxu +6 more
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WRA-Net: Wide Receptive Field Attention Network for Motion Deblurring in Crop and Weed Image. [PDF]
Plant Phenomics, 2023 Yun C, Kim YH, Lee SJ, Im SJ, Park KR.
europepmc +1 more source
Image Motion Deblurring Based on Deep Residual Shrinkage and Generative Adversarial Networks. [PDF]
Comput Intell Neurosci, 2022 Jiang W, Liu A.
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Motion streak facilitates motion deblurring
Journal of Vision, 2022 Seonggyu Choe +3 more
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A Video Deblurring Algorithm Based on Motion Vector and An Encorder-Decoder Network
IEEE Access, 2019 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.
Shanqing Zhang +5 more
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