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Chaowei Shan - IEEE Xplore Author Profile

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Author details

Chaowei Shan

Publications

4

Citations

99

Publications by Year

20182022

Co-Authors:

Omer Faruk AdilAitor Alvarez-GilaCodruta O. AncutiCosmin AncutiMarcelo Bertalmo

Show All Co-Authors (69)

Chaowei Shan

Affiliation

Department of Electronic Engineering and Information Science

University of Science and Technology of China

Hefei, China

Publication Topics

Convolutional Neural Network,
Generative Adversarial Networks,
Final Results,
Gaussian Noise,
Image Pairs,
Input Image,
Peak Signal-to-noise Ratio,
Raw Images,
Single Image,
Ablation Experiments,
Additive Noise,
Advanced Driver Assistance Systems

Biography

Chaowei Shan received the B.S. degree in electronic information engineering from Xidian University in 2017, and the M.S. degree in information and communication engineering from the University of Science and Technology of China in 2020. His research interests include image and video processing.(Based on document published on 28 December 2021).

Publications

4

Citations

99

Publications by Year

20182022

Co-Authors:

Omer Faruk Adil
Aitor Alvarez-Gila
Codruta O. Ancuti
Cosmin Ancuti
Marcelo Bertalmo

Show All Co-Authors (69)

Author's Published Works

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Showing 1-4 of 4 results

Conferences (3)

Journals (1)

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Single Year
Zhibo Chen(4)
Chaowei Shan(4)
Xin Jin(3)
Jiale Chen(2)
Limin Jia(1)
CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China(2)
Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China(1)
Universitat Pompeu Fabra, Spain(1)
University of California at Merced, California, US(1)
USTC (University of Science and Technology of China), China(1)
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
2019 IEEE International Conference on Image Processing (ICIP)(1)
2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)(1)
IEEE Transactions on Image Processing(1)
IEEE(4)
Salt Lake City, UT, USA(1)
Shanghai, China(1)
Taipei, Taiwan(1)
Convolutional Neural Network(4)
Generative Adversarial Networks(3)
Final Results(2)
Gaussian Noise(2)
Image Pairs(2)

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Results

Dual Prior Learning for Blind and Blended Image Restoration

Xin Jin;Li Zhang;Chaowei Shan;Xin Li;Zhibo Chen

IEEE Transactions on Image Processing

Year: 2022 | Volume: 31 | Journal Article |

Cited by: Papers (6)

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Unsupervised single image restoration approach, Deep Image Prior (DIP), aims to restore images by learning enough raw image statistic priors from the corrupted observation. However, it is not uncommon that an image is contaminated by the multiple unknown distortions. Thus it is hard to disentangle the clean and the hybrid distortion signals by solely relying on image prior learning to restore the ...Show More

Dual Prior Learning for Blind and Blended Image Restoration

Xin Jin;Li Zhang;Chaowei Shan;Xin Li;Zhibo Chen

IEEE Transactions on Image Processing

Year: 2022 | Volume: 31 | Journal Article |

A Coarse-to-Fine Framework for Learned Color Enhancement with Non-Local Attention

Chaowei Shan;Zhizheng Zhang;Zhibo Chen

2019 IEEE International Conference on Image Processing (ICIP)

Year: 2019 | Conference Paper |

Cited by: Papers (4)

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Automatic color enhancement are aimed to automaticly and adaptively adjust photos to expected styles and tones. For current learned methods in this field, global harmonious perception and local details are hard to be well-considered in a single model simultaneously. To address this problem, we propose a coarse-to-fine framework with non-local attention for color enhancement in this paper. Within o...Show More

A Coarse-to-Fine Framework for Learned Color Enhancement with Non-Local Attention

Chaowei Shan;Zhizheng Zhang;Zhibo Chen

2019 IEEE International Conference on Image Processing (ICIP)

Year: 2019 | Conference Paper |

AI-GAN: Signal De-Interference via Asynchronous Interactive Generative Adversarial Network

Xin Jin;Zhibo Chen;Jianxin Lin;Wei Zhou;Jiale Chen;Chaowei Shan

2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)

Year: 2019 | Conference Paper |

Cited by: Papers (2)

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Interfering signals, such as rain streak, haze, noise, etc, introduce various types of visibility degradation on original clean signals. Traditional algorithms tackle the signal de-interference problem by the way of signal removal, which usually causes over-smoothness and unexpected artifacts. Hereby, this paper attempts to solve this problem from a totally different perspective of signal decompos...Show More

AI-GAN: Signal De-Interference via Asynchronous Interactive Generative Adversarial Network

Xin Jin;Zhibo Chen;Jianxin Lin;Wei Zhou;Jiale Chen;Chaowei Shan

2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)

Year: 2019 | Conference Paper |

NTIRE 2018 Challenge on Image Dehazing: Methods and Results

Cosmin Ancuti;Codruta O. Ancuti;Radu Timofte;Luc Van Gool;Lei Zhang;Ming-Hsuan Yang;Vishal M. Patel;He Zhang;Vishwanath A. Sindagi;Ruhao Zhao;Xiaoping Ma;Yong Qin;Limin Jia;Klaus Friedel;Sehwan Ki;Hyeonjun Sim;Jae-Seok Choi;Sooye Kim;Soomin Seo;Saehun Kim;Munchurl Kim;Ranjan Mondal;Sanchayan Santra;Bhabatosh Chanda;Jinlin Liu;Kangfu Mei;Juncheng Li;Luyao;Faming Fang;Aiwen Jiang;Xiaochao Qu;Ting Liu;Pengfei Wang;Biao Sun;Jiangfan Deng;Yuhang Zhao;Ming Hong;Jingying Huang;Yizhi Chen;Erin Chen;Xiaoli Yu;Tingting Wu;Anil Genc;Deniz Engin;Hazim Kemal Ekenel;Wenzhe Liu;Tong Tong;Gen Li;Qinquan Gao;Zhan Li;Daofa Tang;Yuling Chen;Ziying Huo;Aitor Alvarez-Gila;Adrian Galdran;Alessandro Bria;Javier Vazquez-Corral;Marcelo Bertalmo;H. Seckin Demir;Omer Faruk Adil;Huynh Xuan Phung;Xin Jin;Jiale Chen;Chaowei Shan;Zhibo Chen

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2018 | Conference Paper |

Cited by: Papers (87)

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This paper reviews the first challenge on image dehazing (restoration of rich details in hazy image) with focus on proposed solutions and results. The challenge had 2 tracks. Track 1 employed the indoor images (using I-HAZE dataset), while Track 2 outdoor images (using O-HAZE dataset). The hazy images have been captured in presence of real haze, generated by professional haze machines. I-HAZE data...Show More

NTIRE 2018 Challenge on Image Dehazing: Methods and Results

Cosmin Ancuti;Codruta O. Ancuti;Radu Timofte;Luc Van Gool;Lei Zhang;Ming-Hsuan Yang;Vishal M. Patel;He Zhang;Vishwanath A. Sindagi;Ruhao Zhao;Xiaoping Ma;Yong Qin;Limin Jia;Klaus Friedel;Sehwan Ki;Hyeonjun Sim;Jae-Seok Choi;Sooye Kim;Soomin Seo;Saehun Kim;Munchurl Kim;Ranjan Mondal;Sanchayan Santra;Bhabatosh Chanda;Jinlin Liu;Kangfu Mei;Juncheng Li;Luyao;Faming Fang;Aiwen Jiang;Xiaochao Qu;Ting Liu;Pengfei Wang;Biao Sun;Jiangfan Deng;Yuhang Zhao;Ming Hong;Jingying Huang;Yizhi Chen;Erin Chen;Xiaoli Yu;Tingting Wu;Anil Genc;Deniz Engin;Hazim Kemal Ekenel;Wenzhe Liu;Tong Tong;Gen Li;Qinquan Gao;Zhan Li;Daofa Tang;Yuling Chen;Ziying Huo;Aitor Alvarez-Gila;Adrian Galdran;Alessandro Bria;Javier Vazquez-Corral;Marcelo Bertalmo;H. Seckin Demir;Omer Faruk Adil;Huynh Xuan Phung;Xin Jin;Jiale Chen;Chaowei Shan;Zhibo Chen

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2018 | Conference Paper |

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