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Pyramid Attention Networks for Image Restoration [article]

Yiqun Mei, Yuchen Fan, Yulun Zhang, Jiahui Yu, Yuqian Zhou, Ding Liu, Yun Fu, Thomas S. Huang, Humphrey Shi
2020 arXiv   pre-print
To solve this problem, we present a novel Pyramid Attention module for image restoration, which captures long-range feature correspondences from a multi-scale feature pyramid.  ...  However, recent advanced deep convolutional neural network based methods for image restoration do not take full advantage of self-similarities by relying on self-attention neural modules that only process  ...  Conclusion In this paper, we proposed a simple and generic pyramid attention for image restoration.  ... 
arXiv:2004.13824v4 fatcat:4tq7ea4ntfdvhazjeqxa3zn7ye

EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration [article]

Ruikang Xu, Zeyu Xiao, Jie Huang, Yueyi Zhang, Zhiwei Xiong
2021 arXiv   pre-print
To address these challenges, we propose an Enhanced Deep Pyramid Network (EDPN) for blurry image restoration from multiple degradations, by fully exploiting the self- and cross-scale similarities in the  ...  Then, the PSA module fuses the above transferred features for subsequent restoration using self- and spatial-attention mechanisms.  ...  [72] propose a dual-branch network to extract features for deblurring and super-resolution and learn a gate module to adaptively fuse the features for image restoration. Attention mechanism.  ... 
arXiv:2105.04872v1 fatcat:4jjp7s5pjbd5flw7ar3sed46qu

PAMSGAN: Pyramid Attention Mechanism-oriented Symmetry Generative Adversarial Network for Motion Image Deblurring

Zhenfeng Zhang
2021 IEEE Access  
VOLUME XX, 2017 1 1) GENERATIVE NETWORK WITH FEATURE PYRAMID ATTENTION The Feature Pyramid Attention (FPA) module [28] realizes the function of extracting pyramid features at three different scales  ...  The generative network adopts the encoding and decoding structure, and introduces the feature pyramid attention mechanism.  ...  ACKNOWLEDGMENT This work is supported by the Project of "Research and development of video acquisition and analysis system for kayak (slalom) motion" in 2020.  ... 
doi:10.1109/access.2021.3099803 fatcat:2jwholnombfx7ebcmojuyzim7q

Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration [article]

Xin Feng, Haobo Ji, Wenjie Pei, Fanglin Chen, David Zhang, Guangming Lu
2022 arXiv   pre-print
In this paper we present a novel model for ultra high-resolution image restoration, referred to as the Global-Local Stepwise Generative Network (GLSGN), which employs a stepwise restoring strategy involving  ...  Extensive experiments across three typical tasks for image background restoration, including image reflection removal, image rain streak removal and image dehazing, show that our GLSGN consistently outperforms  ...  [14] propose the pyramid attention network, which learns self-similarity of noise patterns by a non-local pyramid module. Feng et al.  ... 
arXiv:2207.08808v1 fatcat:bnnjhdsqmvbl7ni7kt744bms5e

Towards Boosting the Channel Attention in Real Image Denoising : Sub-band Pyramid Attention [article]

Huayu Li, Haiyu Wu, Xiwen Chen, Hanning Zhang, Abolfazl Razi
2020 arXiv   pre-print
We equip the SPA blocks on a network designed for real image denoising.  ...  This paper proposes a novel Sub-band Pyramid Attention (SPA) based on wavelet sub-band pyramid to recalibrate the frequency components of the extracted features in a more fine-grained fashion.  ...  the image restoration performance.  ... 
arXiv:2012.12481v1 fatcat:pv3xwuydmzduzgx446jxsqczku

Pyramid Real Image Denoising Network [article]

Yiyun Zhao, Zhuqing Jiang, Aidong Men, Guodong Ju
2019 arXiv   pre-print
To tackle the issue of blind denoising, in this paper, we propose a novel pyramid real image denoising network (PRIDNet), which contains three stages.  ...  While deep Convolutional Neural Networks (CNNs) have shown extraordinary capability of modelling specific noise and denoising, they still perform poorly on real-world noisy images.  ...  To address these issues, we propose a pyramid real image denoising network (PRIDNet) as shown in Fig. 2 .  ... 
arXiv:1908.00273v2 fatcat:ww4xrbmwbncxhp76te2tajbf44

Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting [article]

Yanhong Zeng, Jianlong Fu, Hongyang Chao, Baining Guo
2019 arXiv   pre-print
In this paper, we propose a Pyramid-context ENcoder Network (PEN-Net) for image inpainting by deep generative models.  ...  As the missing content can be filled by attention transfer from deep to shallow in a pyramid fashion, both visual and semantic coherence for image inpainting can be ensured.  ...  In this paper, we propose a Pyramid-context ENcoder Network (PEN-Net) for image inpainting by deep generative models.  ... 
arXiv:1904.07475v4 fatcat:tn7jiz4rrjfdtocgm4yot3sqca

Towards Real-time High-Definition Image Snow Removal: Efficient Pyramid Network with Asymmetrical Encoder-decoder Architecture [article]

Tian Ye, Sixiang Chen, Yun Liu, Yi Ye, Erkang Chen
2022 arXiv   pre-print
We develop a novel Efficient Pyramid Network with asymmetrical encoder-decoder architecture for real-time HD image desnowing.  ...  Recent methods adopt deep neural networks to directly recover clean scenes from snowy images.  ...  It is critical for an image restoration network to exploit clean cues from the latent features effectively.  ... 
arXiv:2207.05605v1 fatcat:6m47kobuo5ghhoajc73wxye26i

Multilevel Feature Exploration Network for Image Superresolution

Xinbo Liu, Ling Wang, Xinyu Chen, Yuqing Liu, Jianping Gou
2022 Scientific Programming  
In this paper, we find that the hierarchical design can effectively restore the structural information and devise a multilevel feature exploration network for image SR (MFSR).  ...  for effective restoration.  ...  Acknowledgments is research was partially supported by the Program for Liaoning Innovation Talents in University (no. LR2019034) and the Overseas Training Foundation of Liaoning (no. 2019GJWYB015).  ... 
doi:10.1155/2022/2014627 fatcat:uxdg3zenbfg45bfokcbvdnlari

Multi-Scale Progressive Fusion Network for Single Image Deraining [article]

Kui Jiang and Zhongyuan Wang and Peng Yi and Chen Chen and Baojin Huang and Yimin Luo and Jiayi Ma and Junjun Jiang
2020 arXiv   pre-print
progressive fusion network (MSPFN) for single image rain streak removal.  ...  Besides, we construct multi-scale pyramid structure, and further introduce the attention mechanism to guide the fine fusion of this correlated information from different scales.  ...  images is progressively aggregated along the pyramid layers and stages of the network.  ... 
arXiv:2003.10985v2 fatcat:7i7klptfxndz7ewbxelv5nrle4

Multi-Scale Progressive Fusion Network for Single Image Deraining

Kui Jiang, Zhongyuan Wang, Peng Yi, Chen Chen, Baojin Huang, Yimin Luo, Jiayi Ma, Junjun Jiang
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
progressive fusion network (MSPFN) for single image rain streak removal.  ...  Besides, we construct multi-scale pyramid structure, and further introduce the attention mechanism to guide the fine fusion of these correlated information from different scales.  ...  images is progressively aggregated along the pyramid layers and stages of the network.  ... 
doi:10.1109/cvpr42600.2020.00837 dblp:conf/cvpr/JiangWY0HL0J20 fatcat:ni2drbsubfadlpyos2tr4fe6sm

BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment [article]

Ziwei Luo, Youwei Li, Shen Cheng, Lei Yu, Qi Wu, Zhihong Wen, Haoqiang Fan, Jian Sun, Shuaicheng Liu
2022 arXiv   pre-print
To achieve this goal, we propose a Pyramid Flow-Guided Deformable Convolution Network (Pyramid FG-DCN) and incorporate Swin Transformer Blocks and Groups as our main backbone.  ...  This work addresses the Burst Super-Resolution (BurstSR) task using a new architecture, which requires restoring a high-quality image from a sequence of noisy, misaligned, and low-resolution RAW bursts  ...  [4] proposed a CNN-based encoder-decoder for RAW burst superresolution and introduced an attention-based fusion into their network.  ... 
arXiv:2204.08332v2 fatcat:zwmo7ssvnngqpdw7k4gpw2ssba

Real-time visual attention on a massively parallel SIMD architecture

Nabil Ouerhani, Heinz Hügli
2003 Real-time imaging  
Conceived for general purpose low-level image processing, ProtoEye consists of a 2D array of mixed analog-digital processing elements.  ...  To reach real-time, the operations required for visual attention computation were optimally distributed on the analog and digital parts.  ...  Norm() is the normalization function. toMem() and restore() are responsible for the image transfers between the PEs and the external memory and vice versa.  ... 
doi:10.1016/s1077-2014(03)00036-6 fatcat:dcbmxqffjjbzhdqgzzl2noqkd4

ASDN: A Deep Convolutional Network for Arbitrary Scale Image Super-Resolution [article]

Jialiang Shen, Yucheng Wang, Jian Zhang
2020 arXiv   pre-print
For SR of small-scales (between 1 and 2), images are constructed by interpolation from a sparse set of precalculated Laplacian pyramid levels.  ...  To obtain a more computationally efficient model for arbitrary scale SR, this paper employs a Laplacian pyramid method to reconstruct any-scale high-resolution (HR) images using the high-frequency image  ...  Laplacian Pyramid Structure The Laplacian Pyramid [3] is used for restoring HR images by preserving residual image information.  ... 
arXiv:2010.02414v1 fatcat:zvn4hsd7vra5biet6eg55vgqfi

EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong, Chen Change Loy
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Second, we propose a Temporal and Spatial Attention (TSA) fusion module, in which attention is applied both temporally and spatially, so as to emphasize important features for subsequent restoration.  ...  Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing attention in the computer vision community.  ...  We thank Yapeng Tian for providing the core codes of TDAN [40] .  ... 
doi:10.1109/cvprw.2019.00247 dblp:conf/cvpr/WangCYDL19 fatcat:3dcfvfjqtbfodb2fxixc3tawte
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