Results 11 to 20 of about 15,641 (253)
High-speed blind structured illumination microscopy via unsupervised algorithm unrolling [PDF]
Nature CommunicationsBlind structured illumination microscopy (blind-SIM) is a valuable tool for achieving super-resolution without the need for known illumination patterns.
Zachary Burns +4 more
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Omniscient Video Super-Resolution [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Most recent video super-resolution (SR) methods either adopt an iterative manner to deal with low-resolution (LR) frames from a temporally sliding window, or leverage the previously estimated SR output to help reconstruct the current frame recurrently. A few studies try to combine these two structures to form a hybrid framework but have failed to give ...
Peng Yi 0002 +6 more
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IEEE Access, 2021 Medical video is important for medical diagnosis. However, due to the influence of the network bandwidth and hardware equipment, some medical videos have low resolution, which is not conducive for diagnosing early diseases with small lesions.
Sheng Ren +3 more
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Iterative Back Projection Network Based on Deformable 3D Convolution
IEEE Access, 2023 Video super-resolution technology enhances the display quality of videos by obtaining high-resolution videos from low-resolution videos. Unlike single-image super-resolution, utilizing information between adjacent video frames is crucial in video super ...
Chengzhi Luo, Bing Li, Feng Liu
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A Lightweight Reconstruction Model via a Neural Network for a Video Super-Resolution Model
Applied Sciences, 2023 Super-resolution in image and video processing has been a challenge in computer vision, with its progression creating substantial societal ramifications.
Xinkun Tang +3 more
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Video Super-Resolution Transformer
CoRR, 2021 Video super-resolution (VSR), with the aim to restore a high-resolution video from its corresponding low-resolution version, is a spatial-temporal sequence prediction problem. Recently, Transformer has been gaining popularity due to its parallel computing ability for sequence-to-sequence modeling.
Jiezhang Cao +3 more
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Video Super-Resolution with Regional Focus for Recurrent Network
Applied Sciences, 2022 Video super-resolution reconstruction is the process of reconstructing low-resolution video frames into high-resolution video frames. Most of the current methods use motion estimation and motion compensation to extract temporal series information, but ...
Yanghui Li +5 more
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Internet Video Delivery Improved by Super-Resolution with GAN
Future Internet, 2022 In recent years, image and video super-resolution have gained attention outside the computer vision community due to the outstanding results produced by applying deep-learning models to solve the super-resolution problem.
Joao da Mata Liborio +2 more
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Super Resolution Reconstruction Algorithm of UAV Image Based on Residual Neural Network
IEEE Access, 2021 With the development of convolutional neural network, video super-resolution algorithm has achieved remarkable success. Because the dependence between frames is complex, traditional methods lack the ability to model the complex dependence, and it is ...
Fang Wan, Xiaorong Zhang
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Frame-Recurrent Video Super-Resolution [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Accepted at CVPR ...
Sajjadi, M., Vemulapalli, R., Brown, M.
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