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Deep Learning for Image Super-Resolution: A Survey [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques ...
Zhihao Wang, Jian Chen, S. Hoi
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Correction to: Single Image Super-Resolution via a Holistic Attention Network [PDF]
European Conference on Computer Vision, 2020 Informative features play a crucial role in the single image super-resolution task. Channel attention has been demonstrated to be effective for preserving information-rich features in each layer.
Ben Niu +8 more
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Feedback Network for Image Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2019 Recent advances in image super-resolution (SR) explored the power of deep learning to achieve a better reconstruction performance. However, the feedback mechanism, which commonly exists in human visual system, has not been fully exploited in existing ...
Z. Li +5 more
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Learning Texture Transformer Network for Image Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2020 We study on image super-resolution (SR), which aims to recover realistic textures from a low-resolution (LR) image. Recent progress has been made by taking high-resolution images as references (Ref), so that relevant textures can be transferred to LR ...
Fuzhi Yang +4 more
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Image Super-resolution Reconstruction Based on Sparse Representation and Guided Filtering [PDF]
Jisuanji gongcheng, 2018 In view of the fact that the image super-resolution reconstruction method cannot effectively reconstruct more high frequency image information in the process of image processing and storage,this paper proposes an image super-resolution reconstruction ...
ZHANG Wanxu,SHI Jianxiong,CHEN Xiaoxuan,WANG Lin,ZHAO Ming,ZHOU Yan,NIU Jinping
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Super-resolution microscopy based on interpolation and wide spectrum de-noising
Компьютерная оптика, 2023 In the conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is approximately equal to the standard deviation of the point spread function.
T. Cheng, T. Chenchen
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Volatile-Nonvolatile Memory Network for Progressive Image Super-Resolution
IEEE Access, 2021 Single-image super-resolution, i.e., reconstructing a high-resolution image from a low-resolution image, is a critical concern in many computer vision applications. Recent deep learning-based image super-resolution methods employ massive numbers of model
Jun-Ho Choi +3 more
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Fast and Accurate Single Image Super-Resolution via Information Distillation Network [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Recently, deep convolutional neural networks (CNNs) have been demonstrated remarkable progress on single image super-resolution. However, as the depth and width of the networks increase, CNN-based super-resolution methods have been faced with the ...
Zheng Hui, Xiumei Wang, Xinbo Gao
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Joint Image Reconstruction and Super-Resolution for Accelerated Magnetic Resonance Imaging
Bioengineering, 2023 Magnetic resonance (MR) image reconstruction and super-resolution are two prominent techniques to restore high-quality images from undersampled or low-resolution k-space data to accelerate MR imaging. Combining undersampled and low-resolution acquisition
Wei Xu +6 more
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Deep Unfolding Network for Image Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2020 Learning-based single image super-resolution (SISR) methods are continuously showing superior effectiveness and efficiency over traditional model-based methods, largely due to the end-to-end training.
K. Zhang, L. Gool, R. Timofte
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