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An Effective Fusion Method to Enhance the Robustness of CNN [article]

Yating Ma, Zhichao Lian
2022 arXiv   pre-print
In this paper, we design a new fusion method to enhance the robustness of CNN.  ...  We use a dot product-based approach to add the denoising module to ResNet18 and the attention mechanism to further improve the robustness of the model.  ...  Inspired by [9] , which integrated channel attention module and spatial attention module in a novel way, we propose a novel defense method combining the denoising module and attention mechanisms.  ... 
arXiv:2205.15582v2 fatcat:axozkl2eurdixldwthfigjs74u

Multi-Scale Adaptive Network for Single Image Denoising [article]

Yuanbiao Gou, Peng Hu, Jiancheng Lv, Xi Peng
2022 arXiv   pre-print
In this paper, we reveal this missing piece for multi-scale architecture design and accordingly propose a novel Multi-Scale Adaptive Network (MSANet) for single image denoising.  ...  Multi-scale architectures have shown effectiveness in a variety of tasks including single image denoising, thanks to appealing cross-scale complementarity.  ...  To summarize, the contributions are as follows: • We propose a novel neural network for single image denoising, termed as MSANet.  ... 
arXiv:2203.04313v1 fatcat:kerhniycfbh5ll5qxo73ia7pu4

Multi-Perspective Anomaly Detection [article]

Manav Madan, Peter Jakob, Tobias Schmid-Schirling, Abhinav Valada
2021 arXiv   pre-print
We employ different augmentation techniques with a denoising process to deal with scarce one-class data, which further improves the performance (ROC AUC = 80\%).  ...  function for anomaly detection.  ...  Acknowledgments: We sincerely thank the Inline Vision Systems group for the discussions and the provision of the experimental platform. We thank Oier Mees for the additional supervision.  ... 
arXiv:2105.09903v1 fatcat:u2kffutaenbujm6yua5udhigge

Front Matter: Volume 11878

Xudong Jiang, Hiroshi Fujita
2021 Thirteenth International Conference on Digital Image Processing (ICDIP 2021)  
Publication of record for individual papers is online in the SPIE Digital Library.  ...  using a Base 36 numbering system employing both numerals and letters.  ...  for multi-category analysis on heart sound 11878 10 A tampering detection algorithm based on multi-scrambling coding 11878 11 An improved generative adversarial network for remote sensing image denoising  ... 
doi:10.1117/12.2603859 fatcat:7iznff73tze2fdyoz2qy6ookpu

CLEARER: Multi-Scale Neural Architecture Search for Image Restoration

Yuanbiao Gou, Boyun Li, Zitao Liu, Songfan Yang, Xi Peng
2020 Neural Information Processing Systems  
Different from the existing labor-intensive handcrafted architecture design paradigms, we present a novel method, termed as multi-sCaLe nEural ARchitecture sEarch for image Restoration (CLEARER), which  ...  is a specifically designed neural architecture search (NAS) for image restoration.  ...  Conclusion In this paper, we propose a novel NAS method which is specifically designed for image restoration in a differentiable manner.  ... 
dblp:conf/nips/GouLLY020 fatcat:dvrqmjldjffnpf7i7vwi2prcr4

DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval [article]

Aichun Zhu, Zijie Wang, Yifeng Li, Xili Wan, Jing Jin, Tian Wang, Fangqiang Hu, Gang Hua
2021 arXiv   pre-print
In order to adequately utilize multi-modal and multi-granular information for a higher retrieval accuracy, five diverse alignment paradigms are adopted.  ...  A surroundings-person separation and fusion mechanism plays the key role to realize an accurate and effective surroundings-person separation under a mutually exclusion constraint.  ...  Alignment paradigms. To adequately utilize multi-modal and multi-granular information for a higher retrieval accuracy, five different alignment paradigms are adopted.  ... 
arXiv:2109.05534v1 fatcat:ffagkml6gfge5fzrzqxydwc3ua

Multi-Perspective Anomaly Detection

Peter Jakob, Manav Madan, Tobias Schmid-Schirling, Abhinav Valada
2021 Sensors  
We employ different augmentation techniques with a denoising process to deal with scarce one-class data, which further improves the performance (ROC AUC =80%).  ...  function for anomaly detection.  ...  Acknowledgments: We sincerely thank the Inline Vision Systems group for the discussions and the provision of the experimental platform. We thank Oier Mees for the discussions.  ... 
doi:10.3390/s21165311 pmid:34450753 pmcid:PMC8399776 fatcat:wwa5h5we3fcifobdpegur4mvdy

Multi-Stage Progressive Image Restoration [article]

Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao
2021 arXiv   pre-print
The resulting tightly interlinked multi-stage architecture, named as MPRNet, delivers strong performance gains on ten datasets across a range of tasks including image deraining, deblurring, and denoising  ...  Our main proposal is a multi-stage architecture, that progressively learns restoration functions for the degraded inputs, thereby breaking down the overall recovery process into more manageable steps.  ...  Depending on the task complexity, we scale the network width by setting the number of channels to 40 for deraining, 80 for denoising, and 96 for deblurring.  ... 
arXiv:2102.02808v2 fatcat:3ipxs74e55gwzauqlegl56ok6m

Generic 3D Convolutional Fusion for image restoration [article]

Jiqing Wu, Radu Timofte, Luc Van Gool
2016 arXiv   pre-print
This complementarity motivated us to propose a novel 3D convolutional fusion (3DCF) method.  ...  Also recently, exciting strides forward have been made in the area of image restoration, particularly for image denoising and single image super-resolution.  ...  Conclusions We propose a novel 3D convolutional fusion (3DCF) network for image restoration.  ... 
arXiv:1607.07561v1 fatcat:7kmezqwrdjd3dk7hhep4xc37za

Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution [article]

Oleksii Sidorov, Jon Yngve Hardeberg
2019 arXiv   pre-print
However, the latter becomes an issue for hyperspectral image processing where datasets commonly consist of just a few images.  ...  In this work, we propose a new approach to denoising, inpainting, and super-resolution of hyperspectral image data using intrinsic properties of a CNN without any training.  ...  The majority of hyperspectral super-resolution (SR) algorithms perform a fusion of input hyperspectral image with a high-resolution multispectral image which is easier to obtain [11] [25] .  ... 
arXiv:1902.00301v2 fatcat:bbxosl6tdzcnjexxgfa22demvy

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 5677-5686 Fast Multi-Scale Structural Patch Decomposition for Multi-Exposure Image Fusion.  ...  ., +, TIP 2020 8226-8237 Deep Guided Learning for Fast Multi-Exposure Image Fusion.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Concurrent Video Denoising and Deblurring for Dynamic Scenes

Efklidis Katsaros, Piotr K. Ostrowski, Daniel Wesierski, Anna Jezierska
2021 IEEE Access  
INDEX TERMS deblurring, denoising, multi-task learning, video enhancement  ...  Our contribution is threefold: a) We propose R2-D4, a multi-scale encoder architecture attached to two cascaded decoders performing the restoration task in two steps. b) We design multi-scale residual  ...  MULTI-TASK LEARNING Multi-task Learning constitutes the paradigm where different tasks are learnt simultaneously [33] , typically through hardparameter sharing.  ... 
doi:10.1109/access.2021.3129602 fatcat:hzh3hmuiwzfnlb3aadzinni5ea

Table of contents

2020 IEEE Transactions on Image Processing  
Ko 4721 DRPL: Deep Regression Pair Learning for Multi-Focus Image Fusion .................................................... 9190 Sequential Dual Attention Network for Rain Streak Removal in a Single  ...  Wang 157 Multi-Channel and Multi-Model-Based Autoencoding Prior for Grayscale Image Restoration ............................ ....................................................................... S.  ... 
doi:10.1109/tip.2019.2940373 fatcat:i7hktzn4wrfz5dhq7hj75u6esa

TANet: A new Paradigm for Global Face Super-resolution via Transformer-CNN Aggregation Network [article]

Yuanzhi Wang, Tao Lu, Yanduo Zhang, Junjun Jiang, Jiaming Wang, Zhongyuan Wang, Jiayi Ma
2021 arXiv   pre-print
In this paper, we propose a novel paradigm based on the self-attention mechanism (i.e., the core of Transformer) to fully explore the representation capacity of the facial structure feature.  ...  Specifically, we design a Transformer-CNN aggregation network (TANet) consisting of two paths, in which one path uses CNNs responsible for restoring fine-grained facial details while the other utilizes  ...  Self-calibrated Multi-path Fusion Network for Local Representation The local representation path in Figure 2 shows the architecture of the proposed SMFN, which contains G self-calibrated multi-path fusion  ... 
arXiv:2109.08174v1 fatcat:g6257a5ksjesra6ff5ltmv3lne

Adaptive Context-Tree-Based Statistical Filtering for Raster Map Image Denoising

Minjie Chen, Mantao Xu, Pasi Franti
2011 IEEE transactions on multimedia  
Filtering of raster map images is chosen as a case study of a more general class of palette-indexed images for the denoising problem of images with a discrete number of output colors.  ...  We apply a universal statistical filter using context-tree modeling via a selective context expansion capturing those pixel combinations that are present in the image.  ...  Morillas for providing the code of his algorithm.  ... 
doi:10.1109/tmm.2011.2166538 fatcat:jecled7kdbckxkvc7bcifo2xka
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