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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
[article]
2020
arXiv
pre-print
Preserved Fulltext
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. ...
The challenge is a new version of the previous NTIRE 2019 challenge on real image denoising that was based on the SIDD benchmark. ...
Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, Oppo, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich.
A. Teams and ...
arXiv:2005.04117v1
fatcat:iwtpyxikerbqhhvkpmwghqxeke
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
[article]
2020
arXiv
pre-print
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This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. ...
The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. ...
Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, Oppo, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich. ...
arXiv:2005.01996v1
fatcat:ewngd7chdve3fbvwis32v64ruq
Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising
[article]
2020
arXiv
pre-print
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Experiments on both synthetic and real-world noisy images show that our PT-MWRN performs favorably against the state-of-the-art denoising methods in terms both quantitative metrics and visual quality. ...
to denoising results. ...
In NTIRE 2019 Challenge on Real Image Denoising [46] , GRDN [47] , DHDN [24] and DIDN [48] have won the first three places on the sRGB track. ...
arXiv:2010.12422v1
fatcat:3ojm6hu6c5c3xotsawomiz6nri
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise
[article]
2021
arXiv
pre-print
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Consequently, we show that our FBI-Denoiser blindly trained solely based on single noisy images can achieve the state-of-the-art performance on several real-world noisy image benchmark datasets with much ...
We consider the challenging blind denoising problem for Poisson-Gaussian noise, in which no additional information about clean images or noise level parameters is available. ...
Note that MCU-Net is also a strong baseline that ranked high in the NTIRE 2020 Challenge on Real Image Denoising -Track1: rawRGB. ...
arXiv:2105.10967v1
fatcat:pahb53mvhrgenj22gr5ljrmnza
Self-Supervised training for blind multi-frame video denoising
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2004.06957v3 fatcat:xy7rxrvkyffzpfwfqulwaq2oviOther Versions
We demonstrate this by showing results on blind denoising of different synthetic and realistic noises. ...
We propose a self-supervised approach for training multi-frame video denoising networks. These networks predict frame t from a window of frames around t. ...
The second, more challenging, dataset consists of ten sequences of 120 frames each extracted from the training dataset for the NTIRE 2020 Video Quality Mapping Challenge. 4 Following [2] all the sequences ...
arXiv:2004.06957v4
fatcat:tyzktotytrhmfezjxdvtovmcnq
Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes
[article]
2020
arXiv
pre-print
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Experimental results demonstrate that our method outperforms state-of-the-art video and raw image denoising algorithms on both indoor and outdoor videos. ...
In recent years, the supervised learning strategy for real noisy image denoising has been emerging and has achieved promising results. ...
The winner of NTIRE 2019 Real Image Denoising Challenge proposed a Bayer preserving augmentation method for raw image denoising, and achieved state-of-the-art denoising results [23] . ...
arXiv:2003.14013v1
fatcat:ksp64aeqovdyvk5gaipdeixv2u
Superkernel Neural Architecture Search for Image Denoising
[article]
2020
arXiv
pre-print
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We demonstrate the effectiveness of our method on the SIDD+ benchmark for image denoising. ...
In this paper, we focus on exploring NAS for a dense prediction task that is image denoising. ...
, (part of NTIRE 2020 Challenge on Real Image Denoising [2, 11, 1]) dataset for image denoising achieving state-of-the-art results. 2. Related work
2.1. ...
arXiv:2004.08870v1
fatcat:72jlvuqczncxzbnyfn4gxmskgm
DRNet: A Deep Neural Network With Multi-layer Residual Blocks Improves Image Denoising
2021
IEEE Access
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For real image denoising, we use training images released by the NTIRE 2020 Real Image Denoising Challenge-Track2: sRGB, which are from the SIDD dataset [46] . ...
FIGURE 5 . 5 Denoising results on the image Monarch from the Set12 with different noise level
FIGURE 6 . 6 Denoising results of different methods on one image from the Kodak24 with σ = 50: (a) noisy ...
doi:10.1109/access.2021.3084951
fatcat:atxek5cihbhwbiihcv5uytj2eq
SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution
[article]
2020
arXiv
pre-print
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We submitted our method in NTIRE 2020 super-resolution challenge and won 1st in PSNR, 2nd in SSIM, and 13th in LPIPS. ...
By allowing multiple LR images, we build a set of pseudo pairs by denoising and downsampling LR images and cast the original unsupervised problem into a supervised learning problem but in one level lower ...
This work was supported by NAVER Corporation and also by the National Research Foundation of Korea grant funded by the Korea government (MSIT) (no.NRF-2019R1A2C1006608) ...
arXiv:2004.11020v1
fatcat:4r5xru6zzbdz3ezgucrj5yzofi
NTIRE 2020 Challenge on NonHomogeneous Dehazing
[article]
2020
arXiv
pre-print
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This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). ...
We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze free and nonhomogeneous hazy images recorded outdoor. ...
Teams and affiliations
NTIRE 2020 team
Title:
NTIRE 2020 Challenge on Nonhomogeneous
Dehazing
Members:
Codruta
O. ...
arXiv:2005.03457v1
fatcat:3j6klhwog5bi3powihxdlrjgeq
Hierarchical Regression Network for Spectral Reconstruction from RGB Images
[article]
2020
arXiv
pre-print
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We evaluate proposed HRNet with other architectures and techniques by participating in NTIRE 2020 Challenge on Spectral Reconstruction from RGB Images. ...
The HRNet is the winning method of track 2 - real world images and ranks 3rd on track 1 - clean images. ...
4
Testing result on NTIRE 2020 challenge The proposed HRNet ranks 3rd and 1st on track 1 and track 2, respectively, of NTIRE 2020 Spectral Reconstruction from RGB Images Challenge [4] . ...
arXiv:2005.04703v1
fatcat:ge45kuwmafcrrj2ki7cfoftwti
Generative Adversarial Networks for Image Super-Resolution: A Survey
[article]
2022
arXiv
pre-print
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Next, we compare performance of these popular GANs on public datasets via quantitative and qualitative analysis in SISR. ...
Recent generative adversarial networks (GANs) can achieve excellent results on low-resolution images with small samples. However, there are little literatures summarizing different GANs in SISR. ...
2020 Real World SR challenge [173] NTIRE 2020 Real World SR challenge [173] USISResNet [129] NTIRE-2020 Real-world SR Challenge validation dataset [173] , DIV2K [151] , Flickr2k [152] , KADID ...
arXiv:2204.13620v1
fatcat:hlwdqith65cxrbqrnbphjz6u4u
NTIRE 2020 Challenge on Image and Video Deblurring
[article]
2020
arXiv
pre-print
Preserved Fulltext
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Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on Image and Video Deblurring. ...
The winning methods demonstrate the state-ofthe-art performance on image and video deblurring tasks. ...
Acknowledgments We thank the NTIRE 2020 sponsors: HUAWEI Technologies Co. Ltd., OPPO Mobile Corp., Ltd., Voyage81, MediaTek Inc., DisneyResearch|Studios, and ETH Zurich (Computer Vision Lab). ...
arXiv:2005.01244v2
fatcat:aoy3tyxlybefrd7yd5ywvr6jh4
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
[article]
2020
arXiv
pre-print
Preserved Fulltext
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This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. ...
The methods were ranked in terms of their fidelity, measured using the peak signal-to-noise ratio (PSNR) between the ground truth clean images and the restored images produced by the participants' methods ...
Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, OPPO, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich. ...
arXiv:2005.03155v1
fatcat:7cob4jufzbawfafcimgtoitdk4
Moire Image Restoration using Multi Level Hyper Vision Net
[article]
2020
arXiv
pre-print
Preserved Fulltext
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The proposed algorithms has been tested with the NTIRE 2020 challenge dataset and thus achieved 36.85 and 0.98 Peak to Signal Noise Ratio (PSNR) and Structural Similarity (SSIM) Index respectively. ...
A moire pattern in the images is resulting from high frequency patterns captured by the image sensor (colour filter array) that appear after demosaicing. ...
Experimental Results The proposed architecture has been trained and validated with the NTIRE 2020 challenge dataset [26] . The shared NTIRE 2020 dataset consists of 10000 images. ...
arXiv:2004.08541v1
fatcat:e4emtpphc5cqdfqkt7ifrh7l6y
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