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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)
2020 arXiv   pre-print
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]

Andreas Lugmayr, Martin Danelljan, Radu Timofte, Namhyuk Ahn, Dongwoon Bai, Jie Cai, Yun Cao, Junyang Chen, Kaihua Cheng, SeYoung Chun, Wei Deng, Mostafa El-Khamy (+34 others)
2020 arXiv   pre-print
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]

Yali Peng, Yue Cao, Shigang Liu, Jian Yang, Wangmeng Zuo
2020 arXiv   pre-print
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]

Jaeseok Byun, Sungmin Cha, Taesup Moon
2021 arXiv   pre-print
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]

Valéry Dewil, Jérémy Anger, Axel Davy, Thibaud Ehret, Pablo Arias, Gabriele Facciolo
2021 arXiv   pre-print
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]

Huanjing Yue, Cong Cao, Lei Liao, Ronghe Chu, Jingyu Yang
2020 arXiv   pre-print
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]

Marcin Możejko, Tomasz Latkowski, Łukasz Treszczotko, Michał Szafraniuk, Krzysztof Trojanowski
2020 arXiv   pre-print
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

Jiahong Zhang, Yonggui Zhu, Wenyi Li, Wenlong Fu, Lihong Cao
2021 IEEE Access  
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]

Namhyuk Ahn and Jaejun Yoo and Kyung-Ah Sohn
2020 arXiv   pre-print
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]

Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu, Radu Timofte, Jing Liu, Haiyan Wu, Yuan Xie, Yanyun Qu, Lizhuang Ma, Ziling Huang, Qili Deng, Ju-Chin Chao (+40 others)
2020 arXiv   pre-print
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]

Yuzhi Zhao, Lai-Man Po, Qiong Yan, Wei Liu, Tingyu Lin
2020 arXiv   pre-print
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]

Chunwei Tian, Xuanyu Zhang, Jerry Chun-Wen Lin, Wangmeng Zuo, Yanning Zhang
2022 arXiv   pre-print
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]

Seungjun Nah, Sanghyun Son, Radu Timofte, Kyoung Mu Lee
2020 arXiv   pre-print
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]

Shanxin Yuan, Radu Timofte, Ales Leonardis, Gregory Slabaugh, Xiaotong Luo, Jiangtao Zhang, Yanyun Qu, Ming Hong, Yuan Xie, Cuihua Li, Dejia Xu, Yihao Chu (+34 others)
2020 arXiv   pre-print
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]

D.Sabari Nathan and M.Parisa Beham and S. M. Md Mansoor Roomi
2020 arXiv   pre-print
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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