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Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation [article]

Jiaming Liu, Chi-Hao Wu, Yuzhi Wang, Qin Xu, Yuqian Zhou, Haibin Huang, Chuan Wang, Shaofan Cai, Yifan Ding, Haoqiang Fan, Jue Wang
<span title="2019-07-30">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
sources, and subsequently how to perform valid data augmentation with raw images.  ...  Towards this end, we present a Bayer preserving augmentation (BayerAug) method as an effective approach for raw image augmentation.  ...  Demonstration of our proposed (a) Bayer pattern unification and (b) Bayer preserving augmentation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.12945v2">arXiv:1904.12945v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xixhjw4yrzcxzmzx3xohytnihu">fatcat:xixhjw4yrzcxzmzx3xohytnihu</a> </span>
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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results [article]

Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte, Michael S. Brown, Yue Cao, Zhilu Zhang, Wangmeng Zuo, Xiaoling Zhang, Jiye Liu, Wendong Chen, Changyuan Wen, Meng Liu (+78 others)
<span title="2020-05-08">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This challenge has two tracks for quantitatively evaluating image denoising performance in (1) the Bayer-pattern rawRGB and (2) the standard RGB (sRGB) color spaces.  ...  This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results.  ...  Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, Oppo, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich. A. Teams and  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.04117v1">arXiv:2005.04117v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iwtpyxikerbqhhvkpmwghqxeke">fatcat:iwtpyxikerbqhhvkpmwghqxeke</a> </span>
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CycleISP: Real Image Restoration via Improved Data Synthesis [article]

Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao
<span title="2020-03-17">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
It allows us to produce any number of realistic image pairs for denoising both in RAW and sRGB spaces.  ...  Consequently, image denoising algorithms are mostly developed and evaluated on synthetic data that is usually generated with a widespread assumption of additive white Gaussian noise (AWGN).  ...  Using the Bayer unification and augmentation technique [39] , we randomly perform horizontal and vertical flips.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.07761v1">arXiv:2003.07761v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iuxskjr4fvhcbbtszlitm4tkr4">fatcat:iuxskjr4fvhcbbtszlitm4tkr4</a> </span>
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Feature-Align Network with Knowledge Distillation for Efficient Denoising [article]

Lucas D. Young, Fitsum A. Reda, Rakesh Ranjan, Jon Morton, Jun Hu, Yazhu Ling, Xiaoyu Xiang, David Liu, Vikas Chandra
<span title="2021-03-18">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We propose an efficient neural network for RAW image denoising.  ...  Although neural network-based denoising has been extensively studied for image restoration, little attention has been given to efficient denoising for compute limited and power sensitive devices, such  ...  The latter two datasets are unified into an RGGB pattern with Bayer Unification [25] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.01524v2">arXiv:2103.01524v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4vf2kf7xrrenbkskhjy3lngrrq">fatcat:4vf2kf7xrrenbkskhjy3lngrrq</a> </span>
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Table of Contents

<span title="">2019</span> <i title="IEEE"> 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) </i> &nbsp;
missing) and Arnav Bhavsar (missing) Gayatri Joshi (missing), Romi Phadte (missing), Paras Jain (missing), Adaptive Labeling for Deep Learning to Hash 621 Image Denoising Using Deep CGAN With Bi-Skip Connections  ...  Friedhoff (missing) Online Reconstruction of Indoor Scenes With Local Manhattan Frame Growing 964 Deep Metric Learning for Identification of Mitotic Patterns of HEp-2 Cell Images 1080 Krati Gupta (missing  ...  Learning Raw Image Denoising With Bayer Pattern Unification and Bayer Preserving Augmentation 2070 Jiaming Liu (missing) , Chi-Hao Wu (missing) , Yuzhi Wang (missing) , Qin Xu (missing), Yuqian Zhou  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2019.00004">doi:10.1109/cvprw.2019.00004</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h7xpqwyrofdxniqtxbodn66mpy">fatcat:h7xpqwyrofdxniqtxbodn66mpy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717215552/https://ieeexplore.ieee.org/ielx7/8972688/9025328/09025462.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/01/60/0160a5461e71d14655ec8525ed68a0607a80b840.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2019.00004"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

DeepSelfie: Single-shot Low-light Enhancement for Selfies

Yucheng Lu, Dong-Wook Kim, Seung-Won Jung
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
To train the selfie enhancement network, we also introduce a method of synthesizing pairs of noisy and dark raw selfie images and their corresponding well-illuminated images.  ...  His main research interests include image enhancement, 3-D model reconstruction, and machine learning-based computer vision applications.  ...  In [16] , Bayer pattern unification was proposed to denoise different Bayer patterns of raw images. From the degraded raw image, multiple image processing operations can be applied together.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3006525">doi:10.1109/access.2020.3006525</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zltwzuo5cveqhnebufpcajl3py">fatcat:zltwzuo5cveqhnebufpcajl3py</a> </span>
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Dynamic Mathematics for Automated Machine Learning Techniques [article]

Nicholas Kuo, University, The Australian National
<span title="2021-08-31">2021</span>
However, modern machine learning techniques such as backpropagation training was firmly established in 1986 while computer vision was revolutionised in 2012 with the introduction of AlexNet.  ...  This thesis is our effort to develop and to understand ways to automate machine learning. Specifically, we focused on Recurrent Neural Networks (RNNs), Meta-Learning, and Continual Learning.  ...  In contrast, the MetaSGD meta-learner augmented existing gradient descent schemes by learning a learning rate per parameter.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.25911/zmy2-7160">doi:10.25911/zmy2-7160</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/flnkwfv33rbupg2e5m4twnbaie">fatcat:flnkwfv33rbupg2e5m4twnbaie</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220423010401/https://openresearch-repository.anu.edu.au/bitstream/1885/246708/1/Kuo_AnuPhdThesis2021.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/35/50/3550349e720c932a07ecccc01ed605a081693560.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.25911/zmy2-7160"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>