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NTIRE 2020 Challenge on NonHomogeneous Dehazing

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arxiv 2005.03457 v1 pith:STIZAM4G submitted 2020-05-07 cs.CV

NTIRE 2020 Challenge on NonHomogeneous Dehazing

Codruta O. Ancuti , Cosmin Ancuti , Florin-Alexandru Vasluianu , Radu Timofte , Jing Liu , Haiyan Wu , Yuan Xie , Yanyun Qu
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Lizhuang Ma Ziling Huang Qili Deng Ju-Chin Chao Tsung-Shan Yang Peng-Wen Chen Po-Min Hsu Tzu-Yi Liao Chung-En Sun Pei-Yuan Wu Jeonghyeok Do Jongmin Park Munchurl Kim Kareem Metwaly Xuelu Li Tiantong Guo Vishal Monga Mingzhao Yu Venkateswararao Cherukuri Shiue-Yuan Chuang Tsung-Nan Lin David Lee Jerome Chang Zhan-Han Wang Yu-Bang Chang Chang-Hong Lin Yu Dong Hongyu Zhou Xiangzhen Kong Sourya Dipta Das Saikat Dutta Xuan Zhao Bing Ouyang Dennis Estrada Meiqi Wang Tianqi Su Siyi Chen Bangyong Sun Vincent Whannou de Dravo Zhe Yu Pratik Narang Aryan Mehra Navaneeth Raghunath Murari Mandal
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classification cs.CV
keywords hazenonhomogeneouschallengedehazingimagesdatasethazyimage
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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. NH-Haze is the first realistic nonhomogeneous haze dataset that provides ground truth images. The nonhomogeneous haze has been produced using a professional haze generator that imitates the real conditions of haze scenes. 168 participants registered in the challenge and 27 teams competed in the final testing phase. The proposed solutions gauge the state-of-the-art in image dehazing.

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