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NTIRE 2020 Challenge on NonHomogeneous Dehazing

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 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
This paper reviews the NTIRE 2020 Challenge on Non-Homogeneous 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.  ...  Acknowledgments We thank the NTIRE 2020 sponsors: HUAWEI Technologies Co. Ltd., OPPO Mobile Corp., Ltd., Voy-age81, MediaTek Inc., DisneyResearch|Studios, and ETH  ... 
doi:10.1109/cvprw50498.2020.00253 dblp:conf/cvpr/AncutiAVTLWXQMH20 fatcat:gb67yyqfovdpnly7bfwz2t5rne

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

Knowledge Transfer Dehazing Network for NonHomogeneous Dehazing

Haiyan Wu, Jing Liu, Yuan Xie, Yanyun Qu, Lizhuang Ma
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
The KTDN ranks 2 nd 2 nd 2 nd in NTIRE-2020 NonHomogeneous Dehazing Challenge [4, 5].  ...  Single image dehazing is an ill-posed problem that has recently drawn important attention. It is a challenging image process task, especially in nonhomogeneous scene.  ...  Our method remains some haze in dehazing images, but obtains a relatively pleasing visual effect. NTIRE-2020 NonHomogeneous Dehazing Challenge.  ... 
doi:10.1109/cvprw50498.2020.00247 dblp:conf/cvpr/WuLXQM20 fatcat:bh7nxaicsffyvcesfefrtcnca4

Trident Dehazing Network

Jing Liu, Haiyan Wu, Yuan Xie, Yanyun Qu, Lizhuang Ma
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Our method won the first place in NTIRE2020 nonhomogeneous dehazing challenge.  ...  Most existing dehazing methods are not robust to nonhomogeneous haze.  ...  Only our proposed TDN reconstructs faithful and sharp hazy free results with little artifact and good perceptual quality on all commonly used dehazing benchmarks. NTIRE-2020 Dehazing Challenge.  ... 
doi:10.1109/cvprw50498.2020.00223 dblp:conf/cvpr/LiuWXQM20 fatcat:6kle3kkzkvaojktg5qhnsod3py

NonLocal Channel Attention for NonHomogeneous Image Dehazing

Kareem Metwaly, Xuelu Li, Tiantong Guo, Vishal Monga
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Experiments performed on challenging benchmark datasets of NTIRE'20 and NTIRE'18 demonstrate that the proposed method -namely, AtJwD-can outperform many state-of-the-art alternatives in the sense of quality  ...  The emergence of deep learning methods that complement traditional model-based methods has helped achieve a new state-of-the-art for image dehazing.  ...  In NTIRE'20 nonhomogeneous dehazing challenge [7] , the proposed AtJwD and AtJwD+ (see Section 5 for details) obtain highly competitive dehazing results with AtJwD in particular achieving the best performance  ... 
doi:10.1109/cvprw50498.2020.00234 dblp:conf/cvpr/MetwalyLGM20 fatcat:xllniudzlnckfdf2blrzl2g5tq

Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing [article]

Sourya Dipta Das, Saikat Dutta
2020 arXiv   pre-print
Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.  ...  Finally, we show the superiority of this network on Dense Haze Removal to other state-of-the-art models.  ...  challenge on NonHomogeneous Im- age Dehazing: 4.6.3 Dense Haze Removal: Table 2: NTIRE 2020 Nonhomogeneous challenge [5] Leaderboard.  ... 
arXiv:2005.05999v1 fatcat:jsamgnc5rrel3nkxmjhtet7kwa

NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images

Codruta O. Ancuti, Cosmin Ancuti, Radu Timofte
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
This is the first nonhomogeneous image dehazing dataset and contains 55 outdoor scenes.  ...  The objective performance evaluation of the dehazing methods is one of the major obstacles due to the lacking of a reference dataset.  ...  Acknowledgments Part of this work has been supported by 2020 European Union Research and Innovation Horizon 2020 under the grant agreement Marie Sklodowska-Curie No 712949 (TECNIOspring PLUS), as well  ... 
doi:10.1109/cvprw50498.2020.00230 dblp:conf/cvpr/AncutiAT20 fatcat:poabmgrrrrbdxnngkrlouwhx5i

Ensemble Dehazing Networks for Non-homogeneous Haze

Mingzhao Yu, Venkateswararao Cherukuri, Tiantong Guo, Vishal Monga
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Image dehazing is one of the most challenging imaging inverse problems.  ...  Experiments performed on challenging benchmark image datasets of NTIRE'20 and NTIRE'19 demonstrate that the proposed models outperform many state-of-the-art methods and this fact is particularly demonstrated  ...  Based on PSNR, EDN-EDU model ranks 7 th in the NTIRE-2020 Dehazing Challenge, while being 7 th in the SSIM metric.  ... 
doi:10.1109/cvprw50498.2020.00233 dblp:conf/cvpr/YuCGM20 fatcat:ezanxdrusrcedbq44psix5fsua

Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing

Sourya Dipta Das, Saikat Dutta
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.  ...  Finally, we show the superiority of this network on Dense Haze Removal to other state-of-the-art models.  ...  2020 Nonhomogeneous Image Dehazing challenge in our experiments.  ... 
doi:10.1109/cvprw50498.2020.00249 dblp:conf/cvpr/DasD20 fatcat:lpreusw3pvhknibpqdllgcsf3y

NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images [article]

Codruta O. Ancuti, Cosmin Ancuti, Radu Timofte
2020 arXiv   pre-print
The objective performance evaluation of the dehazing methods is one of the major obstacles due to the lacking of a reference dataset.  ...  Image dehazing is an ill-posed problem that has been extensively studied in the recent years.  ...  Acknowledgments Part of this work has been supported by 2020 European Union Research and Innovation Horizon 2020 under the grant agreement Marie Sklodowska-Curie No 712949 (TECNIOspring PLUS), as well  ... 
arXiv:2005.03560v1 fatcat:sxaipoz4cvb2raw5my2vwiczum

DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing [article]

Minghan Fu, Huan Liu, Yankun Yu, Jun Chen, Keyan Wang
2021 arXiv   pre-print
Firstly, due to the complicated haze distribution, texture details are easy to be lost during the dehazing process.  ...  To tackle these two issues, we introduce a novel dehazing network using 2D discrete wavelet transform, namely DW-GAN.  ...  TDN is the winner method in NTIRE 2020 NonHomogeneous Dehazing Challenge. Quantitative Results Comparison. The experiment results are shown in Table. 2.  ... 
arXiv:2104.08911v2 fatcat:7cnprpthpvgjbljrur2ycrml2i

NTIRE 2020 Challenge on Image and Video Deblurring

Seungjun Nah, Sanghyun Son, Radu Timofte, Kyoung Mu Lee, Yu Tseng, Yu-Syuan Xu, Cheng-Ming Chiang, Yi-Min Tsai, Stephan Brehm, Sebastian Scherer, Dejia Xu, Yihao Chu (+36 others)
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
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.  ...  In this challenge, we present the evaluation results from 3 competition tracks as well as the proposed solutions.  ...  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).  ... 
doi:10.1109/cvprw50498.2020.00216 dblp:conf/cvpr/NahSTLTXCTBSXCS20 fatcat:a6ojyfuidrbb3avwdpv4mje77e

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.  ...  In this challenge, we present the evaluation results from 3 competition tracks as well as the proposed solutions.  ...  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 Perceptual Extreme Super-Resolution: Methods and Results

Kai Zhang, Shuhang Gu, Radu Timofte, Taizhang Shang, Qiuju Dai, Shengchen Zhu, Tong Yang, Yandong Guo, Younghyun Jo, Sejong Yang, Seon Joo Kim, Lin Zha (+51 others)
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results.  ...  The challenge task was to super-resolve an input image with a magnification factor ×16 based on a set of prior examples of low and corresponding high resolution images.  ...  Acknowledgements We thank the NTIRE 2020 sponsors: HUAWEI, OPPO, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich.  ... 
doi:10.1109/cvprw50498.2020.00254 dblp:conf/cvpr/ZhangGTSDZYGJYK20 fatcat:yvicfxmotjbhfk72f2noujonlq

Haze Relevant Feature Attention Network for Single Image Dehazing

Xin Jiang, Lu Lu, Ming Zhu, Zhicheng Hao, Wen Gao
2021 IEEE Access  
It is worth noting that the NH-Haze dataset has been employed by the IEEE CVPR 2020 NTIRE workshop associated challenge on image dehazing [31] . B.  ...  The proposed method is also evaluated on NH-Haze dataset, which contains paired nonhomogeneous hazy and corresponding haze free images.  ... 
doi:10.1109/access.2021.3100604 fatcat:fzuwr36mtvhu5a47kadxzo5ciq
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